Fountain Code based Adaptive Multi-hop Reliable Data Transfer for Underwater Acoustic Networks
|
|
- Brendan Gerard Hopkins
- 6 years ago
- Views:
Transcription
1 Fountain Code based Adaptive Multi-hop Reliable Data Transfer for Underwater Acoustic Networs Zhong Zhou 1, Haining Mo 1, Yibo Zhu 1, Zheng Peng 1, Jie Huang 2 and Jun-Hong Cui 1 {zhongzhou, haining.mo, yibo.zhu, zhengpeng, jhuang, jcui}@engr.uconn.edu 1 Computer Science & Engineering Department, University of Connecticut, Storrs, CT Electrical & Computer Engineering Department, University of Connecticut, Storrs, CT Abstract In this paper, we investigate multi-hop reliable data transfer for underwater acoustic networs. We propose a new protocol, called FOuntain Code based Adaptive multi-hop Reliable data transfer (FOCAR. FOCAR is essentially a hybrid ARQ scheme which integrates Fountain codes with hop-by-hop retransmission-upon-failure. It considers the half duplex nature of the underwater acoustic modems and adapts the bloc size of each hop to optimize the end-to-end delay for the multi-hop networ scenario. Extensive simulation results show that FOCAR can achieve high reliability with low end-to-end delay and high energy efficiency. I. INTRODUCTION As an emerging area, underwater acoustic networ has attracted rapidly growing interests in last several years [1], [2], [3]. The unique characteristics of underwater acoustic communication have posed significant challenges for the protocol design on each layer of the networs. In this paper, we tacle a challenging yet unsolved problem, multi-hop reliable data transfer, for underwater acoustic networs. Generally, underwater networs are characterized by long propagation delays, error-prone channel and low available bandwidth. In addition, current underwater acoustic modems are half-duplex and the state transition delay between transmitting and receiving is significant (ranging from hundreds of milliseconds to several seconds [4], [5]. These features mae conventional methods for reliable data transfer undesirable for underwater acoustic networs. First, end-to-end approaches are inefficient since a transmission failure on any one hop leads to a retransmission from the source to the sin over multiple hops, which significantly increases the average end-to-end delay. Second, even with hop by hop methods, one retransmission can largely degrade overall system performance given the large propagation and state transition delay. Finally, although some pioneering studies, such as [6], have investigated hybrid ARQ schemes for reliable data transfer in underwater acoustic networs, they have not taen into consideration the large state transition delay within the acoustic modems. These schemes do not optimize for the multi-hop scenario, where one hop with poor lin quality can become the bottlenec lin in the whole system and starve subsequent hops with good lin qualities. Inspired by the thoughts and ideas discussed above, in this paper, we propose a new scheme, called FOuntain Code based Adaptive multi-hop Reliable data transfer (FOCAR for underwater acoustic networs. FOCAR is a hybrid scheme which integrates coding with retransmission-upon-failure. Fountain codes are used due to their strong error correction capability and rateless property. The integration with a selective repeat based retransmission scheme can greatly reduce the delay within one hop. In addition, FOCAR proposes an optimization framewor to imize the end-to-end delay over multiple hops. Further, FOCAR considers the impact of the large state transition delay within current acoustic modems, which has been neglected by prior research wor. The rest of this paper is organized as follows. In Section II, we first review some bacground nowledge and related wor. Then in Section III, we describe FOCAR in detail. After that, we present simulation results in Section IV. We finally conclude our paper in Section V. II. RELATED WORK Reliable data transfer has been extensively investigated for terrestrial wireless networs. In [7], Wan et al. proposed PSFQ protocol, which employs a hop-by-hop ARQ lie approach with fast data rate for retransmission. In [8], a protocol, ESRT was investigated. Due to the distinctions between underwater acoustic networs and terrestrial radio networs, these protocols are unsuitable for the underwater environment. Recently, efficient reliable data transfer for underwater acoustic networs has received significant research interests. The authors in [9] analyze three inds of stop-and-wait protocols for underwater acoustic networs and shows that the performance of the basic stop-and-wait protocols can be significantly improved by transmitting pacets in group and selective acnowledgment. In [10], fountain code is employed to facilitate the reliability and efficiency of broadcasting in underwater acoustic networs. A mathematical model on the performance of fountain codes for broadcasting is given in this paper. In [11], a fountain code based reliable data transport and storage protocol for underwater acoustic networs is proposed. A concatenated fountain coding mechaniss employed. While sensing-zone fountain code is utilized to enable reliable data transport, a second layer of fountain code is used to guarantee uniform storage reliability. In [6], a hop-by-hop hybrid ARQ scheme, called SDRT, was proposed for underwater acoustic networs. In SDRT, the sender first divides pacets into multiple blocs. It then encodes each bloc using a simple version of Tornado codes and transmits pacets fast inside a window. After that, it slows down data transmission, waiting for the response from the receiver. If the sender does not get a positive ACK from the receiver, it will send one and only one coded pacet to the receiver after it times out. No negative ACK is used in SDRT. When the underwater acoustic channel is in deep fading, such a single pacet retransmission scheme is ignorant of the current channel condition and thus very inefficient. In addition, SDRT and most existing researches ignore the large state transition delay of the underwater acoustic modems, which
2 2 has significant impacts on multi-hop reliable data transfer in underwater acoustic networs. III. PROTOCOL DESCRIPTION In this section, we first introduce Fountain Codes and present the networ model. Then, we describe our FOCAR protocol in detail. A. Fountain Codes Fountain codes are record-breaing codes for channels with erasures (e.g., pacet losses in a communication networ. It has enabled a revolutionary way of non-flow-based data delivery over unreliable networs, pioneered by the invention of LT codes [12] and Raptor codes [13]. The basic idea of a Digital Fountain code is as follows. The encoder is a fountain that produces an endless supply of water drops (encoded pacets. Suppose the original source file has a size of K pacets, and each drop contains l encoded pacet. A receiver that wishes to receive the encoded file holds a bucet to collect drops until the number of drops in the bucet is K (which is a little larger than K, and then it can recover the original file. Fountain codes are rateless in the sense that the number of encoded pacets that can be generated from a source message is potentially limitless. In addition, the number of encoded pacets generated can be detered on the fly. Furthermore, another attractive feature of fountain codes is that they are nown to have efficient encoding and decoding algorithms [12], [13]. In this paper, we choose Fountain codes for the coding process of FOCAR. On the one hand, Fountain codes have very efficient encoding and decoding algorithms with linear complexity [12], [13], which could help to reduce the overall end-to-end delay. On the other hand, the amount of redundancy can be detered on the fly, which will greatly facilitate the implementation of selective repeat, directly contributing to low end-to-end delays and high energy efficiency. B. Networ Model The target multi-hop underwater acoustic networ is illustrated in Fig. 1. From a source to a destination, there exists a multi-hop path. How to obtain the path is discussed in Section III-F. On the path, the ith node is defined as node i, its next hop as node i + 1, and its previous hop as node i 1. Each node is equipped with only one half-duplex underwater acoustic modem, where the state transition delay between the sending and receiving states is not negligible any more [4], [5]. And during the modem state transition, the node can neither send nor receive any data. Further, on each node, there is a First In First Out (FIFO queue to store all pacets. Any pacet cog from the upper layer or from the upper stream node will first be fed into this queue. When it is time for transmission, the node fetches pacets frots queue head and sends them out. C. Protocol Overview As mentioned earlier, FOCAR is essentially a hybrid ARQ scheme, smartly integrating Fountain codes and retransmission-upon-failure to improve the system reliability and efficiency. FOCAR includes two essential components: per-hop reliable data transfer and multi-hop optimization. The per-hop reliable data transfer wors as follows: Referring to Fig. 1, on node i, after it receives pacets from node source Node i-1 Node i Node i+1 Destination Fig. 1. Illustration of the networ model i 1, it will first group pacets into one bloc ( is defined as the data bloc size of node i. Then it will code the pacets in each bloc into M pacets with Fountain codes (M is defined as the coded pacet bloc size. Note that for the ease of design, M is the same for every node. After that, node i sends the M coded pacets to node i + 1 and switches to receiving status. If node i + 1 can correctly decode the original data pacets (it has received equal to or more than coded pacets, it will send a positive ACK to node i. Otherwise, node i + 1 will send a negative ACK (indicating the number of unrecovered pacets to node i. The sender, node i, based on the negative ACK information, will transmit more coded pacets to the receiver node i + 1. If node i + 1 can receive pacets out of all the coded pacets sent out by node i in this retransmission, all the original data pacets can be recovered. From the above description, we can see that appropriately setting is very critical: if is large, the coding rate will be reduced, which results in more retransmissions on node i; on the other hand, if is small, the queueing delay on node i will be increased, which also degrades the system performance. This brings us to the second component of FOCAR: multi-hop optimization. In order to optimize the data bloc size on every node, FOCAR first collects the pacet error rate information of every hop from the source to the destination. Then, it solves an approximate convex optimization problem (detailed in Section III-E to get the optimal solutions. After that, it will distribute the optimal solution to every node. How to couple this multi-hop optimization with routing in a distributed way is discussed in Section III-F. Next, we will first analyze the per-hop reliable data transfer. Then we will present the multi-hop optimization. After that, we will discuss the distributed implementation of FOCAR. D. Per-hop Reliable Data Transfer Obviously, to reduce the number of retransmissions, we need to mae sure that every transmission of the coded pacets within one hop can be successfully decoded with a high probability. With Fountain codes, we can safely assume that if the receiver can correctly receive pacets from the M coded pacets, it can correctly recover the original data pacets [12], [13]. If we denote the unsuccessful decoding probability for one transmission as δ (note that δ is a system design parameter, we can have =0 (p e i M (1 p e i δ, (1 where p e is the pacet error rate of the acoustic channel from node i to node i+1. This equation also applies during the retransmission process. When the sender receives a negative
3 3 ACK from the receiver, which includes the number of coded pacets that are needed for correct decoding, it sets in Eq.(1 to and calculates the number of coded pacets for its next retransmission. With Eq. (1, we now that the receiver can correctly recover the original data pacets at least with probability after every transmission or retransmission. Intuitively, to reduce the retransmission delay, δ usually taes a very small value. Thus, the average transmission delay d i for data pacets to be correctly transmitted from node i to node i + 1 can be derived as d i = [( + 2δ( δ 1 ( +...], (2 where is the average time for one-time transmission which includes the transmission time, the signal propagation delay and the transition delay of the acoustic modem between the sending and receiving status. For the ease of analysis, we assume to be the same for every node. Then the average number of the coded pacets, m c i, needed for the successful transmission of data pacets can be written as M M(1 p e m c i i = 1 p e M(1 p e (3 i < i E. Multi-hop Optimization On a multi-hop path, recall that each node has a FIFO queue to store the received pacets from the upper layer or the upstream node. For a node on the path, say node i, when there are more than data pacets in its queue, if it is in the sending status and its next hop, node i + 1, is in the receiving status, then node i will try to code first pacets into M pacets and send them to its next hop. Since the underwater acoustic modem wors in half-duplex mode, any node can be in either sending or receiving status. Let s set the probability that node i sits in the sending status to be p s i. Then it is clear that ps i should be a function of optimal bloc size : a smaller means a larger coding rate and thus means a worse channel condition; to compensate for this, node i should be assigned a larger sending probability if the channel quality between node i and node i+1 is worse. Hence, p s i should be a monotonically decreasing function of. To simplify our analysis, we choose p s i = e M. Since must be smaller than M, p s i lies in (0, 1. Now, the average service rate u i for pacets on node i thus can be derived as u i = p s i p r i+1 = e mi +1 M (1 e M (4 If the input traffic follows a Poisson process, the whole system can be modeled as a Jacson networ since the service time of every node follows exponential distributions approximately. The average queueing delay of a pacet, q i, on node i thus can be derived as: q i = λ u 2 i u i λ (5 where λ is the parameter of the input Poisson process. Now the total delay of a pacet on node i, which includes both queueing delay and transmission delay can be denoted as τ i = q i + (6 Based on the above, we can formulate an optimization problem to imize the average end-to-end delay for a data pacet as follows: q i + i (1,2,...n =0 (p e i M (1 p e i δ 0 M, (7 where n is the number of hops on the studied path. The variables to be optimized in Eq.(7 are the data bloc size for every node. The first constraint specifies that the optimal value of should mae sure that every transmission of M coded pacets can be correctly decoded with high probability. And the second constraint specifies that should be larger than 0 and smaller than the maximal allowable number of coded pacets, M. Since /( does not change with, we can neglect /(1 δ. Combining Eq.(4, Eq.(5 with Eq.(7, we can get i (1..n [e M (1 e +1 M =0 λ 1 δ ] 2 e (p e i M (1 p e i δ M (1 e +1 M (1 δλ 0 M. (8 Again we neglect (/ and tae logarithm on every item. Also we apply the Chernoff s upper bound to the first constraint. Then Eq. (8 can be written as i (1,2,...n logλ log + M log(1 e +1 M log(e e ( (Mp e i 2 2p e i M +1 M (1 e M λ δ 0 M. (9 It should be noted that Eq.(9 is an integer programg problem since can only tae integer values, which is hard to solve efficiently. However, if we relax to tae continuous values, Eq.(9 is a continuous convex optimization problem because the Hessian matrix of both its objective function and its constraints is semi-definitive, which can be efficiently solved by the interior point method [14]. F. Integration with Routing FOCAR can be easily integrated with an on-demand routing protocol (such as AODV lie approach for the distributed implementation. During the routing process of the on-demand routing protocol, the source node can flood a Route Request message to the destination. Any intermediate node who receives this Route Request for the first time will forward it.
4 4 In FOCAR, an intermediate node will insert measured pacet error rate of its acoustic lin in its relayed Route Request message. When the destination node receives an Route Request message which includes the pacet error rates of all the upstream lins, it will first do the multi-hop optimization as in Section III-E to get the optimized data bloc size for every preceding node. Then it will send the optimal solution to every preceding node in its Route Reply message reversely along the path of the corresponding Route Request message. In this way, FOCAR does not need to start a new networ traffic to gather pacet error rates or to distribute optimal data bloc sizes and thus incurs very small communication overhead. Even in highly dynamic environments where channel lin qualities fluctuate frequently, FOCAR is able to gather pacet error rates and distribute optimal solutions in a timely way via routing update messages. IV. PERFORMANCE EVALUATION In this section, we evaluate the performance of FOCAR via simulations. As the baseline, we also implement SDRT [6], which was introduced in Section II, and compare it with FOCAR. A. Simulation Settings We simulate a multi-hop underwater acoustic networ, where multiple nodes are randomly deployed. Unless specified otherwise, the networ parameters are defined as follows: the pacet error rate of every acoustic channel is uniformly distributed between 0.2 and 0.5; the maximum bloc size (or the coded pacet bloc size M is set to be 10; the average number of hops from the source to the destination is 6; and the input traffic on the source node follows a Poisson process with parameter Further, the pacet length is set to be 125 bytes, the bit rate of every node is set to be 1 bps, and the acoustic modem state transition delay is set to be 3 seconds. Two metrics are used to measure the performance: average end-to-end delay and energy efficiency. The former is defined as the average end-to-end delay of a pacet transmitted from the source to the destination. The latter is measured by the average number of coded pacets transmitted along all hops which are needed for the successful end-to-end transmission of one data pacet. B. Simulation Results 1 Impact of Hop Count: In this set of simulations, we change the average number of hops between the source and the destination from 2 to 12 with a step size 2. We run the simulation for 500 rounds and generate 100 pacets in each round. The results on average end-to-end delay and energy efficiency are plotted in Fig. 2 and Fig. 3 respectively. From Fig. 2, we can observe that the average end-toend delay of FOCAR is shorter than that of SDRT. And as the number of hops increases, the delay of FOCAR grows slower than that of SDRT. SDRT does not consider multi-hop optimization. If there is a bad lin with a high pacet error rate on the path from the source to the destination, it will become the bottlenec and pacets will be queued on this lin, which results in high queuing delays. With the increase of the number of hops, the chance of the existence of such a bad lin becomes larger. FOCAR is specially optimized for multi-hop networ scenarios. It optimizes the data bloc size on every node as well as its sending probability p s i, which is defined as a function of. In this way, a bad acoustic channel will be assigned a small bloc size providing it a high coding rate and a high sending probability, which contributes to a larger chance of successful transmission. Thus, FOCAR has a better performance in average end-to-end delay. Fig. 3 shows the comparison of FOCAR with SDRT on the performance of energy efficiency. From this figure, we can see that the energy efficiency of FOCAR is slightly worse but comparable to that of SDRT. We believe this is mainly due to their different pacet retransmission mechanisms. In SDRT, whenever a bloc of pacets fails to be decoded, only one more pacet is retransmitted. After the receiver receives this new coded pacet, if it can correctly recover the original pacets, it will send an ACK and no more pacets are needed. If not, another coded pacet will be sent from the sender. Such a single-pacet retransmission strategy may achieve highest energy efficiency since in most cases, the sender just needs to send the exact number of coded pacets needed for successful decoding. However, this approach can incur a lot of retransmissions on a hop with bad lin quality since the single retransmitted coded pacet can easily get lost. In FOCAR, however, with Fountain codes and negative ACK mechanism, the receiver estimates and ass for multiple pacets for one single retransmission. As a result, the sender may send out more coded pacets than actually needed by the receiver to recover all original pacets. However, Fountain codes can guarantee the number of extra unnecessary coded pacets is very small. Moreover, this strategy can greatly reduce the number of retransmissions. To summarize, compared with SDRT, FOCAR achieves a much better balance between end-to-end delay and energy efficiency. It could guarantee high reliability with low endto-end delay and high energy efficiency. 2 Impact of Traffic Rate λ: In this set of simulations, we investigate the impact of the input traffic rate λ. Fig. 4 and Fig. 5 plot the results on average end-to-end delay and energy efficiency respectively. As illustrated in Fig. 4, with the increase of the input traffic rate λ, the average end-to-end delay of FOCAR stays stable. This is because the input traffic rate is considered in the optimization of FOCAR, which limits their impacts on the delay. On the other hand, in SDRT, the average end-to-end delay for a pacet grows significantly with λ. This is because that a large λ causes significant growth in queueing delay of a pacet on every node. On energy efficiency, from Fig. 5, we can observe that the performance of FOCAR does not vary much when λ increases. For SDRT, the energy efficiency also stays nearly unchanged when λ grows. Since the input traffic rate will not affect the pacet error rate of the channel, the number of coded pacets which are needed for a successful transmission of a data pacet will not change for both FOCAR and SDRT. We have also conducted simulations to evaluate the various parameters for FOCAR, such as the maximum bloc size M, pacet error rate P ER and required unsuccessful decoding probability δ. The simulation results show that FOCAR outperforms SDRT on average end-to-end delay while holding comparable energy efficiency. Due to space limitation, these results are not included in this paper. Interested reader can refer to our technical report [15].
5 5 Fig. 2. Average End-to-End Delay with Varying Number of Hops Fig. 4. Average End-to-End Delay with Varying λ Fig. 3. Energy Efficiency with Varying Number of Hops Fig. 5. Energy Efficiency with Varying λ V. CONCLUSIONS AND FUTURE WORK In this paper, we studied the reliable data transfer for multihop underwater acoustic networs and proposed a new protocol, called Fountain code based adaptive multi-hop reliable data transfer (FOCAR. FOCAR smartly integrates Fountain codes with hop-by-hop retransmission-upon-failure. Further, it taes the half duplex nature of underwater acoustic modems into consideration and is especially optimized for multi-hop networ scenarios. We formulate an optimization framewor to maximize the system performance over multiple hops, and solve the problem by appropriate relaxation. Extensive simulation results show that FOCAR can achieve high reliability with low end-to-end delays and high energy efficiency. Further Wor. We plan to pursue future wor in two directions. 1 In current FOCAR, we assume the average time for one-time transmission is the same for all hops (as the modem status transition delay is doating along the path. It would be interesting to investigate the case that propagation delays are more doating, which will introduce significant complexity to the multi-hop optimization problem. 2 We would lie to explore the real implementation of FOCAR, especially focusing on the coding structure and dynamic channel conditions. Along this path, various underwater testbeds developed at the University of Connecticut will be leveraged. REFERENCES [1] M. Chitre, S. Shahabudeen, and M. Stojanovic, Underwater acoustic communicatin and networs: Recent advances and future challenges, Marine Technology Society Journal, no. 1, pp , [2] J.-H. Cui, J. Kong, M. Gerla, and S. Zhou, Challenges: building scalable mobile underwater wireless sensor networs for aquatic applications, IEEE Networ, Special Issue on Wireless Sensor Networing, vol. 20, pp , May [3] L. Liu, S. Zhou, and J.-H. Cui, Prospects and problems of wireless communication for underwater sensor networs, Wireless Communications & Mobile Computing, vol. 8, pp , [4] L. Freitag, M. Grund, S. singh, J. Partan, P. Kosi, and K. Ball, The WHIO micro-modem: An acoustic communications and navigation system for multiple platforms, in Proceedings of MTS/IEEE OCEANS, vol. 2, pp , June [5] Benthos acoustic modem: [6] P. Xie and J.-H. Cui, An fec-based reliable data transport protocol for underwater sensor networs, in Proceedings of 16th International Conference on Computer Communications and Networs (ICCCN, pp , Aug [7] C.-Y. Wan, A. T. Campbell, and L. Krishnamurthy, PSFQ: A reliable transport protocol for wireless sensor networs, in Proceedings of IEEE WSNA, Sept [8] Y. Sanarasubramainam, O. B. Aan, and I. F. Ayildiz, ESRT: Eventto-sin reliable transport in wireless sensor networs, in Proceedings of ACM Mobihoc, June [9] M. Stojanovic, Optimization of a data lin protocol for an underwater acoustic channel, in Proceedings of MTS/IEEE OCEANS, June [10] P. Casari, M. Rossi, and M. Zorzi, Fountain codes and their application to broadcasting in underwater networs: Performance modeling and relevant tradeoffs, in Proceedings of of ACM WUWNet, Sept [11] R. Cao and L. Yang, Reliable transport and storage protocol with fountain codes for underwater acoustic sensor networs, in WUWNET, (Woods Hole, MA, US, [12] M. Luby, LT codes, in Proceedings of the Annual IEEE Symposium on Foundations of Computer Science, pp , Nov [13] A. Shorollahi, Raptor codes, IEEE Transactions on Information Theory, vol. 52, pp , Jul [14] S. Boyd and L. Vandenberghe, Convex Optimization. Cambridge University Press, [15] Z. Zhou, H. Mo, Y. Zhu, Z. Peng, J. Huang, and J.-H. Cui, Fountain Code based Adaptive Multi-hop Reliable Data Transfer for Underwater Acoustic Networs, in UCONN CSE Technical Report: UbiNet-TR10-02, July 2010.
Fountain Code based Adaptive Multi-hop Reliable Data Transfer for Underwater Acoustic Networks
Fountain Code based Adaptive Multi-hop Reliable Data Transfer for Underwater Acoustic Networks Zhong Zhou 1, Haining Mo 1, Yibo Zhu 1, Zheng Peng 1, Jie Huang 2, Jun-Hong Cui 1 {zhongzhou, haining.mo,
More informationCoding based Multi-hop Coordinated Reliable Data Transfer for Underwater Acoustic Networks: Design, Implementation and Tests
Coding based Multi-hop Coordinated Reliable Data Transfer for Underwater Acoustic Networks: Design, Implementation and Tests Haining Mo, Zheng Peng, Zhong Zhou, Michael Zuba, Zaihan Jiang 2, and Jun-Hong
More informationUW-HARQ: An Underwater Hybrid ARQ Scheme: Design, Implementation and Initial Test
UW-HARQ: An Underwater Hybrid ARQ Scheme: Design, Implementation and Initial Test Haining Mo, Ahmet Can Mingir, Hesham Alhumyani, Yusuf Albayram, and Jun-Hong Cui Computer Science & Engineering Department,
More informationReliable Communication using Packet Coding for Underwater Acoustic Channels
Reliable Communication using Packet Coding for Underwater Acoustic Channels Rameez Ahmed and Milica Stojanovic Northeastern University, Boston, MA 02115, USA Email: rarameez@ece.neu.edu, millitsa@ece.neu.edu
More informationEfficient Error Recovery Using Network Coding in Underwater Sensor Networks
Efficient Error Recovery Using Network Coding in Underwater Sensor Networks Zheng Guo, Bing Wang, and Jun-Hong Cui Computer Science & Engineering Department, University of Connecticut, Storrs, CT, 06269
More informationCHAPTER 5 PROPAGATION DELAY
98 CHAPTER 5 PROPAGATION DELAY Underwater wireless sensor networks deployed of sensor nodes with sensing, forwarding and processing abilities that operate in underwater. In this environment brought challenges,
More informationSURFACE-LEVEL GATEWAY DEPLOYMENT FOR UNDERWATER SENSOR NETWORKS
SURFACE-LEVEL GATEWAY DEPLOYMENT FOR UNDERWATER SENSOR NETWORKS Saleh Ibrahim, Jun-Hong Cui, Reda Ammar {saleh, jcui, reda}@engr.uconn.edu Computer Science & Engineering University of Connecticut, Storrs,
More informationR-MAC: An Energy-Efficient MAC Protocol for Underwater Sensor Networks
R-MAC: An Energy-Efficient MAC Protocol for Underwater Sensor Networks Peng Xie and Jun-Hong Cui UCONN CSE Technical Report: UbiNet-TR06-06 Last Update: June 2007 Abstract Underwater sensor networks are
More informationNetwork coding to combat packet loss in underwater networks
Network coding to combat packet loss in underwater networks Mandar Chitre Department of Electrical & Computer Engineering & ARL, Tropical Marine Science Institute National University of Singapore mandar@arl.nus.edu.sg
More informationA Two-phase Broadcast Scheme for Underwater Acoustic Networks
A Two-phase Broadcast Scheme for Underwater Acoustic Networks Haining Mo, Zheng Peng, Zhong Zhou and Jun-Hong Cui Computer Science & Engineering Department, University of Connecticut, Storrs, CT, USA 6269
More informationA Review Paper On The Performance Analysis Of LMPC & MPC For Energy Efficient In Underwater Sensor Networks
www.ijecs.in International Journal Of Engineering And Computer Science ISSN:2319-7242 Volume 4 Issue 5 May 2015, Page No. 12171-12175 A Review Paper On The Performance Analysis Of LMPC & MPC For Energy
More informationADAPTIVE RTT-DRIVEN TRANSPORT-LAYER FLOW AND ERROR CONTROL. PROTOCOL FOR QoS GUARANTEED IMAGE TRANSMISSION OVER MULTI-
ADAPTIVE RTT-DRIVEN TRANSPORT-LAYER FLOW AND ERROR CONTROL PROTOCOL FOR QoS GUARANTEED IMAGE TRANSMISSION OVER MULTI- HOP UNDERWATER WIRELESS NETWORKS: DESIGN, IMPLEMENTATION, AND ANALYSIS A Thesis by
More informationExperimental Demonstration of Super-TDMA: A MAC Protocol Exploiting Large Propagation Delays in Underwater Acoustic Networks
Experimental Demonstration of Super-TDMA: A MAC Protocol Exploiting Large Propagation Delays in Underwater Acoustic Networks Prasad Anjangi and Mandar Chitre Department of Electrical & Computer Engineering,
More informationNetwork coding to combat packet loss in underwater networks
Network coding to combat packet loss in underwater networks ABSTRACT Mandar Chitre Department of Electrical & Computer Engineering & ARL, Tropical Marine Science Institute National University of Singapore
More informationError Control in Wireless Sensor Networks: A Cross Layer Analysis
University of Nebraska - Lincoln DigitalCommons@University of Nebraska - Lincoln CSE Journal Articles Computer Science and Engineering, Department of 2009 Error Control in Wireless Sensor Networks: A Cross
More informationLecture 7: Sliding Windows. CSE 123: Computer Networks Geoff Voelker (guest lecture)
Lecture 7: Sliding Windows CSE 123: Computer Networks Geoff Voelker (guest lecture) Please turn in HW #1 Thank you From last class: Sequence Numbers Sender Receiver Sender Receiver Timeout Timeout Timeout
More informationUNIT IV -- TRANSPORT LAYER
UNIT IV -- TRANSPORT LAYER TABLE OF CONTENTS 4.1. Transport layer. 02 4.2. Reliable delivery service. 03 4.3. Congestion control. 05 4.4. Connection establishment.. 07 4.5. Flow control 09 4.6. Transmission
More informationOptimizing Packet Size via Maximizing Throughput Efficiency of ARQ on Bluetooth ACL Data Communication Link
Proceedings of the 5th WSEAS Int. Conf. on APPLIED INFOATICS and COUNICATIONS, alta, September -7, 25 (pp24-28 Optimizing Pacet Size via aximizing Throughput Efficiency of AQ on Bluetooth ACL Data Communication
More informationCC-SCTP: Chunk Checksum of SCTP for Enhancement of Throughput in Wireless Network Environments
CC-SCTP: Chunk Checksum of SCTP for Enhancement of Throughput in Wireless Network Environments Stream Control Transmission Protocol (SCTP) uses the 32-bit checksum in the common header, by which a corrupted
More informationAn Enhanced Aloha based Medium Access Control Protocol for Underwater Sensor Networks
An Enhanced Aloha based Medium Access Control Protocol for Underwater Sensor Networks Abdul Gaffar. H 1, a and P.Venkata Krishna 2,b 1 School of Computer Science and Engineering, VIT University, Vellore,
More informationOptimizing Joint Erasure- and Error-Correction Coding for Wireless Packet Transmissions
Optimizing Joint Erasure- and Error-Correction Coding for Wireless Packet Transmissions 2007 IEEE Communication Theory Workshop Christian R. Berger 1, Shengli Zhou 1, Yonggang Wen 2, Peter Willett 1 and
More informationCSC310 Information Theory. Lecture 21: Erasure (Deletion) Channels & Digital Fountain Codes. November 22, 2006 see
CSC310 Information Theory Lecture 21: Erasure (Deletion) Channels & Digital Fountain Codes Sam Roweis Recovering From Erasures 2 How can we recover from erasures? For the BEC, we saw that low-density parity
More informationA JSW-based Cooperative Transmission Scheme for Underwater Acoustic Networks
A JSW-based Cooperative Transmission Scheme for Underwater Acoustic Networks Mingsheng Gao Computing Laboratory National University of Singapore mingsh.gao@gmail.com Hui Jiang Department of Computer Science
More informationFountain Codes Based on Zigzag Decodable Coding
Fountain Codes Based on Zigzag Decodable Coding Takayuki Nozaki Kanagawa University, JAPAN Email: nozaki@kanagawa-u.ac.jp Abstract Fountain codes based on non-binary low-density parity-check (LDPC) codes
More informationNetwork Coding in Underwater Sensor Networks
in Underwater Sensor Networks Claude Manville, Abdulaziz Miyajan, Ayman Alharbi, Haining Mo, Michael Zuba and Jun-Hong Cui Computer Science & Engineering Department, University of Connecticut, Storrs,
More informationCSC310 Information Theory. Lecture 22: Erasure (Deletion) Channels & Digital Fountain Codes. November 30, 2005 see
CSC310 Information Theory Lecture 22: Erasure (Deletion) Channels & Digital Fountain Codes Sam Roweis Recovering From Erasures 2 How can we recover from erasures? For the BEC, we saw that low-density parity
More informationAnalysis of TCP Latency over Wireless Links Supporting FEC/ARQ-SR for Error Recovery
Analysis of TCP Latency over Wireless Links Supporting FEC/ARQ-SR for Error Recovery Raja Abdelmoumen CRISTAL Laboratory, Tunisia Email: Raja.Abdelmoumen@ensi.rnu.tn Chadi Barakat Projet Planète, INRIA-Sophia
More informationCommunications Software. CSE 123b. CSE 123b. Spring Lecture 3: Reliable Communications. Stefan Savage. Some slides couresty David Wetherall
CSE 123b CSE 123b Communications Software Spring 2002 Lecture 3: Reliable Communications Stefan Savage Some slides couresty David Wetherall Administrativa Home page is up and working http://www-cse.ucsd.edu/classes/sp02/cse123b/
More informationHigh-Throughput Multicast Routing Metrics in Wireless Mesh Networks
High-Throughput Multicast Routing Metrics in Wireless Mesh Networks Sabyasachi Roy Dimitrios Koutsonikolas Saumitra Das Y. Charlie Hu TR-ECE-05-7 September, 2005 School of Electrical and Computer Engineering
More informationAqua-Net: An Underwater Sensor Network Architecture: Design, Implementation, and Initial Testing
Aqua-Net: An Underwater Sensor Network Architecture: Design, Implementation, and Initial Testing Zheng Peng, Zhong Zhou, Jun-Hong Cui, Zhijie Jerry Shi {zhengpeng, zhongzhou, jcui, zshi}@engr.uconn.edu
More informationMinimizing Energy Consumption for Cooperative Network and Diversity Coded Sensor Networks
Minimizing Energy Consumption for Cooperative Network and Diversity Coded Sensor Networks Gabriel E. Arrobo and Richard D. Gitlin Department of Electrical Engineering University of South Florida Tampa,
More informationFast distribution of Data in Wireless Sensor Network using Concurrency Operation
Fast distribution of Data in Wireless Sensor Network using Concurrency Operation Geetha N, Janani V Abstract Wireless Sensor Network can be applied in verity of applications in real time. Efficient data
More informationLec 19 - Error and Loss Control
ECE 5578 Multimedia Communication Lec 19 - Error and Loss Control Zhu Li Dept of CSEE, UMKC Office: FH560E, Email: lizhu@umkc.edu, Ph: x 2346. http://l.web.umkc.edu/lizhu slides created with WPS Office
More informationVideo Streaming Over Multi-hop Wireless Networks
Video Streaming Over Multi-hop Wireless Networks Hao Wang Dept. of Computer Information System, Cameron University hwang@cameron.edu Andras Farago, Subbarayan Venkatesan Dept. of Computer Science, The
More informationEnhanced Parity Packet Transmission for Video Multicast using R-DSTC
21st Annual IEEE International Symposium on Personal, Indoor and Mobile Radio Communications Enhanced Parity Packet Transmission for Video Multicast using R-DSTC Özgü Alay, Zhili Guo, Yao Wang, Elza Erkip
More informationSummary of Raptor Codes
Summary of Raptor Codes Tracey Ho October 29, 2003 1 Introduction This summary gives an overview of Raptor Codes, the latest class of codes proposed for reliable multicast in the Digital Fountain model.
More informationResearch Article RLT Code Based Handshake-Free Reliable MAC Protocol for Underwater Sensor Networks
Journal of Sensors Volume 216, Article ID 3184642, 11 pages http://dxdoiorg/11155/216/3184642 Research Article RLT Code Based Handshake-Free Reliable MAC Protocol for Underwater Sensor Networks Xiujuan
More informationEnd-To-End Delay Optimization in Wireless Sensor Network (WSN)
Shweta K. Kanhere 1, Mahesh Goudar 2, Vijay M. Wadhai 3 1,2 Dept. of Electronics Engineering Maharashtra Academy of Engineering, Alandi (D), Pune, India 3 MITCOE Pune, India E-mail: shweta.kanhere@gmail.com,
More informationA Review on Efficient Opportunistic Forwarding Techniques used to Handle Communication Voids in Underwater Wireless Sensor Networks
Advances in Wireless and Mobile Communications. ISSN 0973-6972 Volume 10, Number 5 (2017), pp. 1059-1066 Research India Publications http://www.ripublication.com A Review on Efficient Opportunistic Forwarding
More informationBATS: Achieving the Capacity of Networks with Packet Loss
BATS: Achieving the Capacity of Networks with Packet Loss Raymond W. Yeung Institute of Network Coding The Chinese University of Hong Kong Joint work with Shenghao Yang (IIIS, Tsinghua U) R.W. Yeung (INC@CUHK)
More informationCHAPTER 3 EFFECTIVE ADMISSION CONTROL MECHANISM IN WIRELESS MESH NETWORKS
28 CHAPTER 3 EFFECTIVE ADMISSION CONTROL MECHANISM IN WIRELESS MESH NETWORKS Introduction Measurement-based scheme, that constantly monitors the network, will incorporate the current network state in the
More informationCSE 123: Computer Networks Alex C. Snoeren. HW 1 due NOW!
CSE 123: Computer Networks Alex C. Snoeren HW 1 due NOW! Automatic Repeat Request (ARQ) Acknowledgements (ACKs) and timeouts Stop-and-Wait Sliding Window Forward Error Correction 2 Link layer is lossy
More informationNAMS: A Networked Acoustic Modem System for Underwater Applications
NAMS: A Networked Acoustic Modem System for Underwater Applications Zheng Peng, Haining Mo, Jun Liu, Zuofei Wang, Hao Zhou, Xiaoka Xu, Son Le, Yibo Zhu, Jun-Hong Cui, Zhijie Shi, Shengli Zhou Underwater
More informationQUANTIZER DESIGN FOR EXPLOITING COMMON INFORMATION IN LAYERED CODING. Mehdi Salehifar, Tejaswi Nanjundaswamy, and Kenneth Rose
QUANTIZER DESIGN FOR EXPLOITING COMMON INFORMATION IN LAYERED CODING Mehdi Salehifar, Tejaswi Nanjundaswamy, and Kenneth Rose Department of Electrical and Computer Engineering University of California,
More informationLecture 7: Flow Control"
Lecture 7: Flow Control" CSE 123: Computer Networks Alex C. Snoeren No class Monday! Lecture 7 Overview" Flow control Go-back-N Sliding window 2 Stop-and-Wait Performance" Lousy performance if xmit 1 pkt
More informationThe Design of Degree Distribution for Distributed Fountain Codes in Wireless Sensor Networks
The Design of Degree Distribution for Distributed Fountain Codes in Wireless Sensor Networks Jing Yue, Zihuai Lin, Branka Vucetic, and Pei Xiao School of Electrical and Information Engineering, The University
More informationTransmitting Internet Protocol Packets Efficiently on Underwater Networks using Entropy-Encoder Header Translation
Transmitting Internet Protocol Packets Efficiently on Underwater Networks using Entropy-Encoder Header Translation 5.6 Toby Schneider GobySoft, LLC Woods Hole, MA Email: toby@gobysoft.org Abstract The
More informationF-RTO: An Enhanced Recovery Algorithm for TCP Retransmission Timeouts
F-RTO: An Enhanced Recovery Algorithm for TCP Retransmission Timeouts Pasi Sarolahti Nokia Research Center pasi.sarolahti@nokia.com Markku Kojo, Kimmo Raatikainen University of Helsinki Department of Computer
More informationAn Architecture for Underwater Networks
An Architecture for Underwater Networks Mandar Chitre Acoustic Research Laboratory, National University of Singapore Lee Freitag Woods Hole Oceanographic Institution Ethem Sozer Massachusetts Institute
More informationINTERCONNECTION networks are used in a variety of applications,
1 Randomized Throughput-Optimal Oblivious Routing for Torus Networs Rohit Sunam Ramanujam, Student Member, IEEE, and Bill Lin, Member, IEEE Abstract In this paper, we study the problem of optimal oblivious
More informationOn the Interdependence of Congestion and Contention in Wireless Sensor Networks
On the Interdependence of Congestion and Contention in Wireless Sensor Networks Mehmet C. Vuran Vehbi C. Gungor School of Electrical & Computer Engineering Georgia Institute of Technology, Atlanta, GA
More informationVoid Avoidance in Three-Dimensional Mobile Underwater Sensor Networks
Void Avoidance in Three-Dimensional Mobile Underwater Sensor Networks Peng Xie, Zhong Zhou, Zheng Peng, Jun-Hong Cui, and Zhijie Shi Computer Science & Engineering Department, University of Connecticut,
More informationPerformance Evaluation of Routing Protocols in Wireless Mesh Networks. Motlhame Edwin Sejake, Zenzo Polite Ncube and Naison Gasela
Performance Evaluation of Routing Protocols in Wireless Mesh Networks Motlhame Edwin Sejake, Zenzo Polite Ncube and Naison Gasela Department of Computer Science, North West University, Mafikeng Campus,
More informationAn Efficient Scheduling Scheme for High Speed IEEE WLANs
An Efficient Scheduling Scheme for High Speed IEEE 802.11 WLANs Juki Wirawan Tantra, Chuan Heng Foh, and Bu Sung Lee Centre of Muldia and Network Technology School of Computer Engineering Nanyang Technological
More information3. Evaluation of Selected Tree and Mesh based Routing Protocols
33 3. Evaluation of Selected Tree and Mesh based Routing Protocols 3.1 Introduction Construction of best possible multicast trees and maintaining the group connections in sequence is challenging even in
More information$ " Capacity of Ad Hoc Networks. Physical Layer Issues. Layer 1 Capacity. Path Loss Model. Path Loss Model. Bandwidth of 802.
Capacity of Ad Hoc Networks Quality of Wireless links Physical Layer Issues The Channel Capacity Path Loss Model and Signal Degradation 802.11 MAC for Ad-hoc Networks DCF (Distributed Coordination Function)
More informationPerformance of UMTS Radio Link Control
Performance of UMTS Radio Link Control Qinqing Zhang, Hsuan-Jung Su Bell Laboratories, Lucent Technologies Holmdel, NJ 77 Abstract- The Radio Link Control (RLC) protocol in Universal Mobile Telecommunication
More informationLecture 4: CRC & Reliable Transmission. Lecture 4 Overview. Checksum review. CRC toward a better EDC. Reliable Transmission
1 Lecture 4: CRC & Reliable Transmission CSE 123: Computer Networks Chris Kanich Quiz 1: Tuesday July 5th Lecture 4: CRC & Reliable Transmission Lecture 4 Overview CRC toward a better EDC Reliable Transmission
More informationPRIORITY-BASED BROADCASTING OF SENSITIVE DATA IN ERROR-PRONE WIRELESS NETWORKS
PRIORITY-BASED BROADCASTING OF SENSITIVE DATA IN ERROR-PRONE WIRELESS NETWORKS Pouya Ostovari, Jie Wu, and Ying Dai Center for Networked Computing http://www.cnc.temple.edu Agenda 2 Introduction Motivation
More informationAn Efficient Link Bundling Transport Layer Protocol for Achieving Higher Data Rate and Availability
An Efficient Link Bundling Transport Layer Protocol for Achieving Higher Data Rate and Availability Journal: IET Communications Manuscript ID: COM-2011-0376 Manuscript Type: Research Paper Date Submitted
More informationLecture 10: Link layer multicast. Mythili Vutukuru CS 653 Spring 2014 Feb 6, Thursday
Lecture 10: Link layer multicast Mythili Vutukuru CS 653 Spring 2014 Feb 6, Thursday Unicast and broadcast Usually, link layer is used to send data over a single hop between source and destination. This
More informationGATEWAY MULTIPOINT RELAYS AN MPR-BASED BROADCAST ALGORITHM FOR AD HOC NETWORKS. Ou Liang, Y. Ahmet Şekercioğlu, Nallasamy Mani
GATEWAY MULTIPOINT RELAYS AN MPR-BASED BROADCAST ALGORITHM FOR AD HOC NETWORKS Ou Liang, Y. Ahmet Şekercioğlu, Nallasamy Mani Centre for Telecommunication and Information Engineering Monash University,
More informationSDC: A Distributed Clustering Protocol for Peer-to-Peer Networks
SDC: A Distributed Clustering Protocol for Peer-to-Peer Networks Yan Li 1, Li Lao 2, and Jun-Hong Cui 1 1 Computer Science & Engineering Dept., University of Connecticut, CT 06029 2 Computer Science Dept.,
More informationMinimum Delay Packet-sizing for Linear Multi-hop Networks with Cooperative Transmissions
Minimum Delay acket-sizing for inear Multi-hop Networks with Cooperative Transmissions Ning Wen and Randall A. Berry Department of Electrical Engineering and Computer Science Northwestern University, Evanston,
More informationResearch on Quantitative and Semi-Quantitative Training Simulation of Network Countermeasure Jianjun Shen1,a, Nan Qu1,b, Kai Li1,c
2nd International Conference on Advances in Mechanical Engineering and Industrial Informatics (AMEII 2016) Research on Quantitative and Semi-Quantitative Training Simulation of Networ Countermeasure Jianjun
More informationTransmission Control Protocol (TCP)
TETCOS Transmission Control Protocol (TCP) Comparison of TCP Congestion Control Algorithms using NetSim @2017 Tetcos. This document is protected by copyright, all rights reserved Table of Contents 1. Abstract....
More informationTransmission Control for Fast Recovery of Rateless Codes
Transmission Control for Fast Recovery of Rateless Codes Jau-Wu Huang Department of Computer Science National Tsing Hua University Hsinchu, Taiwan Kai-Chao Yang, Han-Yu Hsieh, Jia-Shung Wang Department
More informationDirect Link Communication I: Basic Techniques. Data Transmission. ignore carrier frequency, coding etc.
Direct Link Communication I: Basic Techniques Link speed unit: bps abstraction Data Transmission ignore carrier frequency, coding etc. Point-to-point link: wired or wireless includes broadcast case Interested
More informationRouting Protocols in MANET: Comparative Study
Available Online at www.ijcsmc.com International Journal of Computer Science and Mobile Computing A Monthly Journal of Computer Science and Information Technology IJCSMC, Vol. 3, Issue. 7, July 2014, pg.119
More informationAnalysis of an automatic repeat request scheme addressing long delay channels
Analysis of an automatic repeat request scheme addressing long delay channels Leonardo Badia, Paolo Casari, Marco Levorato, and Michele Zorzi IMT Lucca Institute for Advanced Studies, piazza S. Ponziano
More informationEfficient Hybrid Multicast Routing Protocol for Ad-Hoc Wireless Networks
Efficient Hybrid Multicast Routing Protocol for Ad-Hoc Wireless Networks Jayanta Biswas and Mukti Barai and S. K. Nandy CAD Lab, Indian Institute of Science Bangalore, 56, India {jayanta@cadl, mbarai@cadl,
More informationPROACTIVE RELIABLE BULK DATA DISSEMINATION IN SENSOR NETWORKS 1
PROACTIVE RELIABLE BULK DATA DISSEMINATION IN SENSOR NETWORKS 1 Limin Wang Sandeep S. Kulkarni Software Engineering and Network Systems Laboratory Department of Computer Science and Engineering Michigan
More informationMAC Protocol Implementation on Atmel AVR for Underwater Communication
MAC Protocol Implementation on Atmel AVR for Underwater Communication - Final Report- Shaolin Peng speng2@ncsu.edu Introduction Underwater acoustic communication is widely used in many areas to collect
More informationPerformance of Multihop Communications Using Logical Topologies on Optical Torus Networks
Performance of Multihop Communications Using Logical Topologies on Optical Torus Networks X. Yuan, R. Melhem and R. Gupta Department of Computer Science University of Pittsburgh Pittsburgh, PA 156 fxyuan,
More informationCS 5520/ECE 5590NA: Network Architecture I Spring Lecture 13: UDP and TCP
CS 5520/ECE 5590NA: Network Architecture I Spring 2008 Lecture 13: UDP and TCP Most recent lectures discussed mechanisms to make better use of the IP address space, Internet control messages, and layering
More informationEnergy Consumption Estimation in Cluster based Underwater Wireless Sensor Networks Using M/M/1 Queuing Model
Energy Consumption Estimation in Cluster based Underwater Wireless Sensor Networks Using M/M/1 Queuing Model Manijeh Keshtgary Reza Mohammadi Mohammad Mahmoudi Mohammad Reza Mansouri ABSTRACT Underwater
More informationAppointed BrOadcast (ABO): Reducing Routing Overhead in. IEEE Mobile Ad Hoc Networks
Appointed BrOadcast (ABO): Reducing Routing Overhead in IEEE 802.11 Mobile Ad Hoc Networks Chun-Yen Hsu and Shun-Te Wang Computer Network Lab., Department of Electronic Engineering National Taiwan University
More informationINTERNATIONAL JOURNAL OF PURE AND APPLIED RESEARCH IN ENGINEERING AND TECHNOLOGY
INTERNATIONAL JOURNAL OF PURE AND APPLIED RESEARCH IN ENGINEERING AND TECHNOLOGY A PATH FOR HORIZING YOUR INNOVATIVE WORK REVIEW ON CONGESTION CONTROL IN WIRELESS SENSOR NETWORK MR. HARSHAL D. WANKHADE,
More informationRouting Protocols in MANETs
Chapter 4 Routing Protocols in MANETs 4.1 Introduction The main aim of any Ad Hoc network routing protocol is to meet the challenges of the dynamically changing topology and establish a correct and an
More informationUsing Hybrid Algorithm in Wireless Ad-Hoc Networks: Reducing the Number of Transmissions
Using Hybrid Algorithm in Wireless Ad-Hoc Networks: Reducing the Number of Transmissions R.Thamaraiselvan 1, S.Gopikrishnan 2, V.Pavithra Devi 3 PG Student, Computer Science & Engineering, Paavai College
More informationA Route Selection Scheme for Multi-Route Coding in Multihop Cellular Networks
A Route Selection Scheme for Multi-Route Coding in Multihop Cellular Networks Hiraku Okada,HitoshiImai, Takaya Yamazato, Masaaki Katayama, Kenichi Mase Center for Transdisciplinary Research, Niigata University,
More informationPerformance Evaluation of Active Route Time-Out parameter in Ad-hoc On Demand Distance Vector (AODV)
Performance Evaluation of Active Route Time-Out parameter in Ad-hoc On Demand Distance Vector (AODV) WADHAH AL-MANDHARI, KOICHI GYODA 2, NOBUO NAKAJIMA Department of Human Communications The University
More informationInterference avoidance in wireless multi-hop networks 1
Interference avoidance in wireless multi-hop networks 1 Youwei Zhang EE228A Project Report, Spring 2006 1 Motivation Wireless networks share the same unlicensed parts of the radio spectrum with devices
More informationAn Energy-Balanced Cooperative MAC Protocol in MANETs
2011 International Conference on Advancements in Information Technology With workshop of ICBMG 2011 IPCSIT vol.20 (2011) (2011) IACSIT Press, Singapore An Energy-Balanced Cooperative MAC Protocol in MANETs
More informationDesign of an Address Assignment and Resolution Protocol for Underwater Networks
Design of an Address Assignment and Resolution Protocol for Underwater Networks Rohit Agrawal Department of EEE and E&I, BITS Pilani-K. K. Birla Goa Campus. Email: f2012267@goa.bits-pilani.ac.in Mandar
More informationImpact of IEEE MAC Packet Size on Performance of Wireless Sensor Networks
IOSR Journal of Electronics and Communication Engineering (IOSR-JECE) e-issn: 2278-2834,p- ISSN: 2278-8735.Volume 10, Issue 3, Ver. IV (May - Jun.2015), PP 06-11 www.iosrjournals.org Impact of IEEE 802.11
More informationLink Scheduling in Multi-Transmit-Receive Wireless Networks
Macau University of Science and Technology From the SelectedWorks of Hong-Ning Dai 2011 Link Scheduling in Multi-Transmit-Receive Wireless Networks Hong-Ning Dai, Macau University of Science and Technology
More informationPERFORMANCE ANALYSIS OF AODV ROUTING PROTOCOL IN MANETS
PERFORMANCE ANALYSIS OF AODV ROUTING PROTOCOL IN MANETS AMANDEEP University College of Engineering, Punjabi University Patiala, Punjab, India amandeep8848@gmail.com GURMEET KAUR University College of Engineering,
More informationPerformance Evaluation of Mesh - Based Multicast Routing Protocols in MANET s
Performance Evaluation of Mesh - Based Multicast Routing Protocols in MANET s M. Nagaratna Assistant Professor Dept. of CSE JNTUH, Hyderabad, India V. Kamakshi Prasad Prof & Additional Cont. of. Examinations
More informationInvestigation on OLSR Routing Protocol Efficiency
Investigation on OLSR Routing Protocol Efficiency JIRI HOSEK 1, KAROL MOLNAR 2 Department of Telecommunications Faculty of Electrical Engineering and Communication, Brno University of Technology Purkynova
More informationImprovement of Buffer Scheme for Delay Tolerant Networks
Improvement of Buffer Scheme for Delay Tolerant Networks Jian Shen 1,2, Jin Wang 1,2, Li Ma 1,2, Ilyong Chung 3 1 Jiangsu Engineering Center of Network Monitoring, Nanjing University of Information Science
More informationImproving the Data Scheduling Efficiency of the IEEE (d) Mesh Network
Improving the Data Scheduling Efficiency of the IEEE 802.16(d) Mesh Network Shie-Yuan Wang Email: shieyuan@csie.nctu.edu.tw Chih-Che Lin Email: jclin@csie.nctu.edu.tw Ku-Han Fang Email: khfang@csie.nctu.edu.tw
More informationReliable and Energy Efficient Protocol for Wireless Sensor Network
Reliable and Energy Efficient Protocol for Wireless Sensor Network Hafiyya.R.M 1, Fathima Anwar 2 P.G. Student, Department of Computer Engineering, M.E.A Engineering College, Perinthalmanna, Kerala, India
More informationImproving Connectivity via Relays Deployment in Wireless Sensor Networks
Improving Connectivity via Relays Deployment in Wireless Sensor Networks Ahmed S. Ibrahim, Karim G. Seddik, and K. J. Ray Liu Department of Electrical and Computer Engineering, and Institute for Systems
More informationPerformance Analysis of TCP LBA and TCP TAHOE Approaches in g Standard Savreet KaurBrar 1, Sandeep Singh Kang 2
Performance Analysis of TCP LBA and TCP TAHOE Approaches in 802.11g Standard Savreet KaurBrar 1, Sandeep Singh Kang 2 1 (MTechCSE Student, Chandigarh Engineering College Landran,India) 2 (Associate Professor
More informationMulticast Transport Protocol Analysis: Self-Similar Sources *
Multicast Transport Protocol Analysis: Self-Similar Sources * Mine Çağlar 1 Öznur Özkasap 2 1 Koç University, Department of Mathematics, Istanbul, Turkey 2 Koç University, Department of Computer Engineering,
More informationObservations on Client-Server and Mobile Agent Paradigms for Resource Allocation
Observations on Client-Server and Mobile Agent Paradigms for Resource Allocation M. Bahouya, J. Gaber and A. Kouam Laboratoire SeT Université de Technologie de Belfort-Montbéliard 90000 Belfort, France
More informationThe Performance of MANET Routing Protocols for Scalable Video Communication
Communications and Network, 23, 5, 9-25 http://dx.doi.org/.4236/cn.23.522 Published Online May 23 (http://www.scirp.org/journal/cn) The Performance of MANET Routing Protocols for Scalable Video Communication
More informationAn Efficient Broadcast Algorithm To Transmit Data In Multi-hop Relay MANETs Fathima Sana 1, Dr. M. Sudheep Elayidom 2
International Journal of Emerging Trends in Science and Technology Impact Factor: 2.838 INC-BEAT 2016 An Efficient Broadcast Algorithm To Transmit Data In Multi-hop Relay MANETs Fathima Sana 1, Dr. M.
More informationAn Implementation of Cross Layer Approach to Improve TCP Performance in MANET
An Implementation of Cross Layer Approach to Improve TCP Performance in MANET 1 Rajat Sharma Pursuing M.tech(CSE) final year from USIT(GGSIPU), Dwarka, New Delhi E-mail address: rajatfit4it@gmail.com 2
More information