Comparison of Analytical and Measured Performance Results on Network Coding in IEEE Ad-Hoc Networks
|
|
- Shona Glenn
- 5 years ago
- Views:
Transcription
1 Comparison of Analytical and Measured Performance Results on Network Coding in IEEE Ad-Hoc Networks Fang Zhao Singapore-MIT Alliance for Research and Technology, Singapore Muriel Médard Department of Electrical Engineering and Research Laboratory of Electronics, MIT Martin Hundebøll, Jeppe Ledet-Pedersen, Stephan A. Rein, Frank H.P. Fitzek Aalborg University, Department of Electronic Systems, Mobile Device Group {mhu, sr, Abstract Network coding is a promising technology that has been shown to improve throughput in wireless mesh networks. In this paper, we compare the analytical and experimental performance of COPE-style network coding in IEEE ad-hoc networks. In the experiments, we use a lightweight scheme called CATWOMAN that can run on standard WiFi hardware. We present an analytical model to evaluate the performance of COPE in simple networks, and our results show the excellent predictive quality of this model. By closely examining the performance in two simple topologies, we observe that the coding gain results from the interaction between network coding and the MAC protocol, and the gap between the theoretical and practical gains is due to the different channel qualities of sending nodes. This understanding is helpful for design of larger mesh networks that use network coding. I. INTRODUCTION Since its introduction by Ahlswede et al. in 2000 [1], network coding has generated much research interest and there have been attempts to apply it to a wide range of networks and applications. Many papers focus on construction of linear or random linear network codes (RLNC), for example, [2], [3], [4], [5], [6], [7]. There also exist works that build simulative setups or illustrate by example the benefits of network coding, e.g. for p2p networks as in [8], [9], [10] and for ad-hoc networks as in [11], [12], [13]. Recently, there have been proposed implementations for coding and decoding algorithms [14], [15], [16] and practical setups for media distribution on current hardware [17], [18]. To apply network coding to wireless mesh networks, Katti et al. [19] introduced a practical and efficient system named COPE, in which packets are XORed together when coding opportunities are found. Experiments were conducted using Linux PCs, and the results show that COPE largely increases network throughput, although it is not optimized for energy consumption. Zhao and Médard gave a theoretical analysis of the COPE performance in [20]. Seferoglu et al. [21] analyzed the performance of TCP over COPE-style wireless networks. Recently, Cloud et al. [22] developed a simple network model that can be used to evaluate the performance of a COPE system. In order to make network coding more readily applicable to real mesh networks, we started a project called CATWOMAN (Coding Applied To Wireless On Mobile Ad-hoc Networks) at Aalborg University. This project is based on an existing routing scheme called BATMAN (Better Approach To Mobile Adhoc Networking), and in a manner that is similar to COPE, it uses XOR network coding. By utilizing the routing information and messages of the BATMAN protocol, network coding can be readily applied on top of an existing ad-hoc protocol. Also, it is a lightweight implementation that can run on standard WiFi hardware. In this paper, we compare the theoretical performance of network coding in mesh networks with the experimental performance obtained using the CATWOMAN scheme and UDP flows. We observe that while the experimental results follow the shape of the theoretical curve nicely, the real coding gain is lower than expected. By focusing on two basic topologies, i.e., Alice and Bob and Crossed Alice and Bob, we are able to gain a good understanding of where the particular gain comes from, and also what causes the gap between the theoretical predictions and practical performance. This knowledge is essential for designing and analyzing large practical mesh networks that use network coding. The remaining of this paper is organized as follows. In Section II we describe the network coding testbed that serves for the experimentation. In Section III and IV, we compare the theoretical and experimental performance of the topologies Alice and Bob and Crossed Alice and Bob, respectively. And finally, we conclude in Section V. II. NETWORK CODING TESTBED In this section we give a brief description of the CAT- WOMAN network coding implementation [23] for ad-hoc networks, and the testbed which we used to conduct the experimental analysis. The implementation uses a new scheme that /12/$ IEEE 43
2 utilizes routing information to discover coding opportunities and the so called promiscuous mode to receive packets. The routing information is obtained via the Originator Messages (OGM), which are periodically sent out by each node to all other nodes in the network. An OGM message contains the address of the OGM originator node and the address of the previous sender. A receiver of an OGM message can thus learn that the originator node is reachable, and its next hop towards the originator. For detection of a coding opportunity, overhearing between neighbor nodes is discovered by utilizing a Time To Live (TTL) field in the originator messages, which is reduced by one each time it is rebroadcasted by a node. If a relay receives two OGM messages with the same originator from two neighbor nodes, and the TTL difference between the two messages is only one, it can conclude that the two neighbor nodes can overhear each other. The relay then updates its list of available packets for each destination node (due to overhearing or being originator of a packet). In the Alice and Bob example, the packets A from Alice and B from Bob are combined, because the packet A is available at destination node Alice, and the packet B at destination node Bob. Broadcast of a coded packet to multiple nodes is achieved via an unicast transmission to a selected destination node, a special packet header format that indicates all the individual destinations. For each node, we enabled promiscuous mode, which allows it to receive any packet (and to forward or discard it upon inspection of the multicast header). The unicast destination node is selected using a link quality estimator derived from the OGM messages, and the weaker link is preferred to favor reliability over throughput. Note that for the unicast link, retransmissions are enabled. The network coding testbed consists of five Open-Mesh OM1P routers, which use the Atheros AR2315 Wireless System-on-a-Chip. The routers are programmed with the open source firmware OpenWRT version RC5 which is extended with the network coding schemes. The nodes are configured to use the IEEE RTS/CTS protocol, a fixed speed of 11 Mbit/s (rate adaptation disabled), and to transmit with a power of 10 dbm. The nodes are placed in a large atrium hall in a University building as illustrated in Figure 1. Bob, Alice, and the relay are placed on the ground floor, and Dave and Charlie on the third floor. Traffic between the nodes is generated by separate Linux Laptops that are connected to each of the nodes. The Linux tool iperf is used to generate traffic with equally spaced 1498 byte UDP packets for 30 seconds at different data rates. The throughput is calculated as the product of the target data rate and the percentage of received packets, e.g., if 90% of the packets have been received and the target data rate is 1 Mbit/s, the calculated throughput is 0.9 Mbit/s. III. COMPARISON OF ALICE AND BOB The Alice and Bob scenario is depicted in Figure 2. Alice and Bob are not able to exchange packets directly and need the help of a relay to forward their packets. In a pure relaying Fig. 1. Testbed of five nodes for the setups Alice and Bob and Crossed Alice and Bob networks. (a) Without network coding (b) With network coding Fig. 2. Exchange of two packets in the Alice and Bob topology with and without network coding. In the transmission schedule diagram, S stands for Send, R for Receive, and B for Broadcast. scenario, the relay would need to forward two packets to Alice and Bob, and we need a total of four transmissions to exchange two packets. Using network coding, the relay XORs two packets from Alice and Bob into one, and broadcasts this coded packet. By doing so, the network coding approach would just need three transmissions instead of four for the exchange. This example can be found in many publications, where a possible performance gain due to network coding of 25% is identified, as one packet out of four is saved. As we will demonstrate in this paper (also shown in [19]) the performance gain is even larger. A. Theoretical Analysis As argued in [20], without network coding, the relay has to send the same number of packets as both Alice and Bob combined. The throughput rises linearly with the offered load until the load equals half of the channel capacity. At that point, Alice and Bob each requires 1/4 of the capacity, and the 44
3 relay requires half of the capacity. From then on, the relay requires more than half of the bandwidth, and the throughput is bounded by the number of packets the relay can forward: BW R = 1 (BW A + BW B ), where BW A, BW B, and BW R are the bandwidths allocated to Alice, Bob, and the relay, respectively. As the network becomes more and more congested, the total throughput drops, until the relay is only allocated with one third of the channel capacity, and Alice and Bob induce a combined load of 2/3. When the offered load increases beyond that point, all three nodes are always backlogged, and as the MAC protocol enforces fairness among the three nodes, the relay nodes would get a constant 1/3 of the capacity. Therefore, the total throughput remains constant at 1/3. at the case where Bob sends at least as many packets as Alice (0 x 0.5). Without network coding, N packets are sent by the relay, and with network coding N x+n((1 x) x), where x represents the proportion of coded packets, and (1 x) x the proportion of not coded packets, resulting in N g C = (1) N x + N((1 x) x) = 1, 0 x 0.5. (2) 1 x If Alice sends more packets than Bob (0.5 <x 1), the number of packets sent in case of network coding is given by N(1 x) +N(x (1 x)), where (1 x) gives the proportion of coded packets and (x (1 x)) the one of not coded packets, resulting in g C = N (3) N(1 x)+n(x (1 x)) = 1, 0.5 <x 1. (4) x Fig. 4. Coding gain as a function of link share for Alice. The coding gain decreases as link share becomes unequal. Fig. 3. Expected throughput for offered load in Alice and Bob topology. Network coding should push the point of congestion and level out. Without network coding, the throughput drops when congestion occurs. When network coding is enabled, each coded packet sent by the relay delivers two packets, one to Alice and one to Bob. Thus, the relay just needs to send half the total number of received packets. In this case, the throughput linearly rises until the relay is allocated one third of the channel capacity, and Alice and Bob are given 1/3 each. The coding gain stays constant at 2 from then on, because the MAC fairness makes sure that the relay keeps one third of the capacity. In case of unequal loads of Alice and Bob, the gain would be determined by the minimum flow, as only these packets can be coded. Figure 3 shows the theoretical coding gain in the Alice and Bob scenario. The above analysis is based on the assumption that the offered load and channel condition for Alice and Bob are symmetrical. When this is not the case, in Figure 4, we illustrate the coding gain for the Alice and Bob scenario as a function of Alice s share of the link. Let g C denote the coding gain, given as the number of packets N the relay would send without network coding divided by the number of packets sent with network coding. If x represents the link share of Alice, the link share of Bob is given as 1 x. We first look B. Experimental Results In Figure 5 the aggregated throughput for Alice and Bob is given. For our testbed we measured a WiFi capacity of 5.2 Mbit/s. Without network coding, the maximum throughput of 2.5 Mbit/s (48% of the capacity) is achieved at 2.8 Mbit/s (53.8% of the capacity), which is in line with our theoretical considerations. For network coding, the achieved throughput only goes up to 3 Mbit/s, which is 57.7% of the capacity, while we expected 5.2 2/3 = 3.47 Mbit/s. For the congested period, the throughput with network coding is roughly 2.7 Mbit/s, while without it is only 1.7 Mbit/s resulting in a gain of 2.7/1.7 =1.6. While we can see from Figures 6 and 7, that the throughput is similar for both Alice (1.4 Mbit/s corresponding to 27% of the capacity) and Bob (1.35 Mbit/s corresponding to 26% of the capacity), the link behavior is yet asymmetric: Figure 8 gives the ratio of coded versus forwarded packets at the relay over the entire range of offered loads. Owing to the asymmetric links, some packets may arrive delayed at the relay, thus missing coding opportunities due to the limited holding time (set to 10 ms). Nevertheless, the simple model shown in Figure 3 and the performance seen in Figures 5 to 7 show excellent concordance, despite the fact that we do not take into account in the 45
4 Fig. 5. Measured aggregated throughput for total offered load in Alice and Bob topology. The coding gain is seen after the network becomes congested. Fig. 7. Measured throughput vs. individual load for Bob. The errors bars show the 95% confidence interval. Fig. 6. Measured throughput vs. individual load for Alice. The error bars show the 95% confidence interval. theoretical model issues such as lost coding opportunities due to delay. IV. COMPARISON OF CROSSED ALICE AND BOB The second example is denoted as the Crossed Alice and Bob topology, see Figure 9. It consists of two bidirectional flows, one between Alice and Dave and the other between Bob and Charlie. All flows again go through the relay node R, and we assume that Alice and Charlie do not overhear each other s transmissions, and neither do Bob and Dave. A. Theoretical Analysis In Figure 10 we illustrate the analytical coding gain for the Crossed Alice and Bob scenario. Without network coding, the relay sends the same number of packets as the nodes combined, and the maximum throughput is achieved when the Fig. 8. Number of forwarded and coded packets vs. throughput for Alice and Bob. The numbers have been normalized such that 1.0 is the number of packets transmitted if coding is was not used. relay and the combined sending nodes each require half of the channel capacity (similar to the Alice and Bob scenario). When the load is further increased, the throughput decreases with the bandwidth allocated to the relay: BW R = 1 (BW A + BW B + BW C + BW D ). The saturation throughput is reached when the relay is allocated with 1/5 of the total bandwidth, and the four other nodes share the remaining 4/5 of the capacity. The throughput stays constant from then on owing to MAC fairness. With network coding, the throughput first increases linearly as in the Alice and Bob scenario, until it achieves a maximum of 2/3 of the capacity when the total offered load is 2/3. From now on the network becomes congested. The throughput however does not stay constant (as in the Alice and Bob scenario) but linearly decreases as the offered load increases 46
5 (a) Without network coding until the relay gets a share of 1/5 of the capacity at a load of 4/5. The throughput then stays constant at 2/5 due to the MAC fairness, which results in a coding gain of 2. B. Experimental Results The experimental results for the Crossed Alice and Bob are given in Figure 11. Without network coding, the throughput peaks to 2.75 Mbit/s (relating to 2.75/5.2 = 53% of the capacity), while it peaks with network coding to 3.5 Mbit/s (relating to 3.5/5.2 = 67% of the capacity), which is in line with the analysis. Also the timing of the two peaks (at 2.75 Mbit/s for not using coding and at 3.55 Mbit/s for using coding, according to 2.75/5.2 = 53% and 3.55/5.2 = 68%, respectively, is as expected by the analysis. Unlike as pre- (b) With network coding Fig. 9. Exchange of two packets between nodes A and D, and two packets between B and C, in a Crossed Alice and Bob network with and without network coding. In the transmission schedule diagram, S stands for Send, R for Receive, and B for Broadcast. Fig. 10. topology. Expected throughput for offered load in Crossed Alice and Bob Fig. 11. Measured aggregated throughput for total offered load in Crossed Alice and Bob topology. dicted, the throughputs (for using / not using coding) both decrease until the minima are reached, given as 2 Mbit/s (2/5.2 = 38% capacity) and 1.5 Mbit/s (1.5/5.2 = 29%), respectively, which is in case of network coding close to the expectation. The coding gain yet peaks only at 1.6 and stabilizes to 1.4, which is illustrated in Figure 12. Again, similarly as in the Alice and Bob scenario, the mistiming of arriving packets, due to unequal link share, reduces some of the coding opportunities. V. CONCLUSION In this paper we compared the analytical and measured performance results of network coding in two basic meshed network topologies. The measured results are obtained on an IEEE testbed implemented on commercial wireless access points. The objective was to compare pure relaying schemes with network coding schemes. The analytical and the measured performance values match pretty well in their basic behavior. However, for high load scenarios, the IEEE hardware platform is causing some remarkable side effects such that the overall gain, estimated by our analytical results, is reduced. For example, in the simple Alice and Bob scenario, 47
6 Fig. 12. Number of forwarded and coded packets vs. throughput for Crossed Alice and Bob. The numbers have been normalized so that 1.0 is the number of packets transmitted if coding is was not used. the system throughput was expected to double, but in our measurements, we only saw a gain of 60%. This reduction is mainly due to the asymmetry of the links, which were assumed to be perfectly symmetric for the analytical case. Furthermore, from our previous measurements of WiFi enabled communication devices, we know that each WiFi node generally has different performance [24]. Also, there might be room for improvement in the implementation itself, which we will look into in our future work. Nevertheless the reported gains in the measurement campaigns are significant, and the understanding we gained through the comparison and analysis will help in designing larger network coded systems in the future. ACKNOWLEDGMENT This work was supported by the Danish Green Mobile Clouds project (project ref. no /FTP) funded by the Danish Council for Independent Research (Sapere Aude programme), the CONE project funded by the Danish Agency for Science, Technology and Innovation (grant no /FTP), and by the National Research Foundation (NRF) of Singapore through the Singapore-MIT Alliance for Research and Technology (SMART) Center for Environmental Sensing and Modeling REFERENCES [1] R. Ahlswede, N. Cai, S.-Y. Li, and R. Yeung, Network information flow, in IEEE Transactions on Information Theory, vol. 46, no. 4, July 2000, pp [2] R. Koetter and M. Médard, An algebraic approach to network coding, in IEEE/ACM Transactions on Networking, vol. 11, no. 5, Oct. 2003, pp [3] S.-Y. Li, R. Yeung, and N. Cai, Linear network coding, vol. 49, no. 2, pp , Feb [4] S.-Y. Li, Q. Sun, and Z. Shao, Linear network coding: Theory and algorithms, in Proceedings of the IEEE, vol. 99, no. 3, March 2011, pp [5] M. Médard, M. Effros, T. Ho, and D. Karger, On coding for nonmulticast networks, in Proc. of Allerton Conf. Commun., [6] D. Traskov, N. Ratnakr, D. Lun, R. Koetter, and M. Médard, Network coding for multiple unicasts: An approach based on linear optimization, in Proc. of the IEEE International Symposium on Information Theory (ISIT 06), July, pp [7] T. Ho, R. Koetter, M. Médard, D. R. Karger, and M. Effros, The benefits of coding over routing in a randomized setting, in Proc. of the IEEE International Symposium on Information Theory (ISIT 04), June [8] Z. Zhang, R. Hou, H. Chen, J. Zhou, and J. Li, Network coding based live peer-to-peer streaming towards minimizing buffering delay, in Proc. of the International Conference on Computer Application and System Modeling (ICCASM 10), vol. 4, oct. 2010, pp. V4 136 V [9] H. Zeng, J. Huang, S. Tao, and W. Cheng, A simulation study on network coding parameters in p2p content distribution system, in Proc. of the International Conference on Communications and Networking in China (ChinaCom 08), Aug. 2008, pp [10] J. Heide and L. Militano, Introduction to network coding for mobile peer to peer (p2p), in Mobile P2P: A Tutorial Guide, F. H. Fitzek and H. Charaf, Eds. John Wiley & Sons, 2009, pp [11] S. Tarapiah, C. Casetti, and C.-F. Chiasserini, Network coding in ad hoc networks: A realistic simulation study, in Proc. of the IEEE INFOCOM Workshops 2009, April 2009, pp [12] C. Campolo, C. Casetti, C.-F. Chiasserini, and S. Tarapiah, Performance of network coding for ad hoc networks in realistic simulation scenarios, in Proc. of the International Conference on Telecommunications (ICT 09), May 2009, pp [13] J. Meng and X. Pan, The optimization study of network coding for coding-aware wireless mesh networks, in Proc. of the International Conference on Future Computer and Communication (ICFCC 10), vol. 2, May 2010, pp. V2 537 V [14] J. Heide, M. Pedersen, F. Fitzek, and M. Médard, On code parameters and coding vector representation for practical rlnc, in Proc. of the IEEE International Conference on Communications (ICC 11), june 2011, pp [15] J. Heide, M. V. Pedersen, and F. Fitzek, Decoding algorithms for random linear network codes, in Proc. of the Int. Conf. on Networking - Workshop on Network Coding Applications and Protocols (NC-Pro 11), May [16] M. Pedersen, J. Heide, and F. H. Fitzek, Kodo: An open and research oriented network coding library, in Proc. of the Int. Conf. on Networking - Workshop on Network Coding Applications and Protocols (NC- Pro 11), May [17] P. Vingelmann, F. Fitzek, M. Pedersen, J. Heide, and H. Charaf, Synchronized multimedia streaming on the iphone platform with network coding, in IEEE Communications Magazine, vol. 49, no. 6, june [18] M. V. Pedersen, J. Heide, F. H. P. Fitzek, and T. Larsen, A mobile application prototype using network coding, in European Transactions on Telecommunications, vol. 21, no. 8, December 2010, pp [19] S. Katti, H. Rahul, W. Hu, D. Katabi, M. Médard, and J. Crowcroft, Xors in the air: practical wireless network coding, in ACM SIGCOMM Comput. Commun. Rev., vol. 36, no. 4, August [20] F. Zhao and M. Médard, On analyzing and improving cope performance, in Proc. of Information Theory and Applications Workshop (ITA), [21] H. Seferoglu and A. Markopoulou, Network coding aware queue management for unicast flows over coded wireless networks, in Proc. of the IEEE International Symposium on Network Coding (NetCod 10), June 2010, pp [22] J. Cloud, L. Zeger, and M. Médard, Effects of mac approaches on non-monotonic saturation with cope - a simple case study, in Proc. of the Military Communications Conference (MILCOM 11), Nov. 2011, pp [23] M. Hundebøll et al., CATWOMAN: Implementation and evaluation of IEEE based multi-hop networks using network coding, in Proc. of the IEEE 76th Vehicular Technology Conference (VTC 12-Fall), Sept [24] M. Petersen, G. Perrucci, and F. Fitzek, Energy and Link Measurements for Mobile Phones using IEEE802.11b/g, in The 4th International Workshop on Wireless Network Measurements (WiNMEE 08) - in conjunction with WiOpt 08, Berlin, Germany, Mar
CATWOMAN: Implementation and Performance Evaluation of IEEE based Multi-Hop Networks using Network Coding
TWOMN: Implementation and Performance Evaluation of IEEE 802.11 based Multi-Hop Networks using Network oding Martin Hundebøll, Jeppe Ledet-Pedersen, Janus Heide, Morten V. Pedersen, Stephan. ein, Frank
More informationPublished in: Computer Aided Modeling and Design of Communication Links and Networks (CAMAD), 2012 IEEE 17th International Workshop on
Aalborg Universitet Energy and Data Throughput for Asymmetric Inter-Session Network Coding Paramanathan, Achuthan; Heide, Janus; Pahlevani, Peyman; Hundebøll, Martin; Rein, Stephan Alexander; Fitzek, Frank
More informationPublished in: 2013 IEEE Consumer Communications & Networking Conference Proceedings
Aalborg Universitet Impact of Network Coding on Delay and Throughput in Practical Wireless Chain Topologies Hundebøll, Martin; Rein, Stephan Alexander; Fitzek, Frank Hanns Paul Published in: 213 IEEE Consumer
More informationEnergy Consumption Model and Measurement Results for Network Coding-enabled IEEE Meshed Wireless Networks
202 IEEE 7th International Workshop on Computer Aided Modeling and Design of Communication Links and Networks (CAMAD) Energy Consumption Model and Measurement Results for Network Coding-enabled IEEE 802.
More informationXORs in the Air: Practical Wireless Network Coding
XORs in the Air: Practical Wireless Network Coding S. Katti, H. Rahul, W. Hu, D. Katabi, M. Medard, J. Crowcroft MIT & University of Cambridge Can we use 3 transmissions to send traffic? 1 2 4 3 Can we
More informationReliable video-streaming delivery in wireless access networks using Network Coding
Reliable video-streaming delivery in wireless access networks using Network Coding MELISA JUNUZOVIĆ, KEMAL ALIČ, ALEŠ ŠVIGELJ Department of Communication Systems, Jozef Stefan Institute Jozef Stefan International
More informationQueue Management for Network Coding in Ad Hoc Networks
2012 Third International Conference on Intelligent Systems Modelling and Simulation Queue Management for Network Coding in Ad Hoc Networks S.E. Tan H.T. Yew M.S. Arifianto I. Saad K.T.K. Teo Modelling,
More informationEffects of MAC Approaches on Non-Monotonic Saturation with COPE - A Simple Case Study
Effects of MAC Approaches on Non-Monotonic Saturation with COPE - A Simple Case Study Jason Cloud*, Linda Zeger, Muriel Médard* *Research Laboratory of Electronics, Massachusetts Institute of Technology,
More informationThe Importance of Being Opportunistic
High Performance Switching and Routing Telecom Center Workshop: Sept 4, 1997. The Importance of Being Opportunistic Sachin Katti Dina Katabi, Wenjun Hu, Hariharan Rahul, and Muriel Medard Bandwidth is
More informationAalborg Universitet. Published in: Communications (ICC), 2014 IEEE International Conference on
Aalborg Universitet On the Coded Packet Relay Network in the Presence of Neighbors Khamfroush, Hana; Pahlevani, Peyman; Roetter, Daniel Enrique Lucani; Hundebøll, Martin; Fitzek, Frank Hanns Paul Published
More informationPublished in: Mobile Wireless Middleware, Operating Systems, and Applications - Workshops
Aalborg Universitet Connecting the islands - enabling global connectivity through local cooperation Heide, Janus; Pedersen, Morten Videbæk; Fitzek, Frank Hanns Paul; Larsen, Torben Published in: Mobile
More informationPictureViewer Pedersen, Morten Videbæk; Heide, Janus; Fitzek, Frank Hanns Paul; Larsen, Torben
Aalborg Universitet PictureViewer Pedersen, Morten Videbæk; Heide, Janus; Fitzek, Frank Hanns Paul; Larsen, Torben Published in: European Wireless 29 DOI (link to publication from Publisher): 1.119/EW.29.5357968
More informationAVALANCHE: A NETWORK CODING ANALYSIS
COMMUNICATIONS IN INFORMATION AND SYSTEMS c 2007 International Press Vol. 7, No. 4, pp. 353-358, 2007 003 AVALANCHE: A NETWORK CODING ANALYSIS RAYMOND W. YEUNG Abstract. In this paper, we study the application
More informationThroughput and Fairness-Aware Dynamic Network Coding in Wireless Communication Networks
Throughput and Fairness-Aware Dynamic Network Coding in Wireless Communication Networks Pouya Ostovari and Jie Wu Department of Computer & Information Sciences, Temple University, Philadelphia, PA 191
More informationAalborg Universitet. Published in: Vehicular Technology Conference (VTC Spring), 2014 IEEE 79th
Aalborg Universitet Sharing the Pi Paramanathan, Achuthan; Pahlevani, Peyman; Thorsteinsson, Simon; Hundebøll, Martin; Roetter, Daniel Enrique Lucani; Fitzek, Frank Hanns Paul Published in: Vehicular Technology
More informationManagement Science Letters
Management Science Letters 4 (2014) 2509 2516 Contents lists available at GrowingScience Management Science Letters homepage: www.growingscience.com/msl Delay-based network coding packet selection Rasoul
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 informationInformation Exchange in Wireless Networks with Network Coding and Physical-layer Broadcast
2005 Conference on Information Sciences and Systems, The Johns Hopkins University, March 16 18, 2005 Information Exchange in Wireless Networks with Network Coding and Physical-layer Broadcast Yunnan Wu
More informationNetwork Coding Efficiency In The Presence Of An Intermittent Backhaul Network
IEEE ICC 2016 - Wireless Communications Symposium Network Coding Efficiency In The Presence Of An Intermittent Backhaul Network Stefan Achleitner, Thomas La Porta Computer Science and Engineering The Pennsylvania
More informationPRESENTED BY SARAH KWAN NETWORK CODING
PRESENTED BY SARAH KWAN NETWORK CODING NETWORK CODING PRESENTATION OUTLINE What is Network Coding? Motivation and Approach Network Coding with Lossless Networks Challenges in Developing Coding Algorithms
More informationNECO: Network Coding Simulator
NECO: Network Coding Simulator Diogo Ferreira 1, Luísa Lima 2, João Barros 1 1 Instituto de Telecomunicações Faculdade de Engenharia da Universidade do Porto 2 Instituto de Telecomunicações Faculdade de
More informationExploiting Sparse Coding: A Sliding Window Enhancement of a Random Linear Network Coding Scheme
Exploiting Sparse Coding: A Sliding Window Enhancement of a Random Linear Network Coding Scheme Pablo Garrido, David Gómez, Jorge Lanza and Ramón Agüero, IEEE Senior Member Universidad de Cantabria, Santander,
More informationPerformance Evaluation of Wireless Network Coding under Practical Settings
Performance Evaluation of Wireless Network Coding under Practical Settings Ihsan A. Qazi Pratik Gandhi Department of Computer Science School of Information Sciences University of Pittsburgh, Pittsburgh,
More informationVolume 2, Issue 4, April 2014 International Journal of Advance Research in Computer Science and Management Studies
Volume 2, Issue 4, April 2014 International Journal of Advance Research in Computer Science and Management Studies Research Article / Paper / Case Study Available online at: www.ijarcsms.com Efficient
More informationWIRELESS networks suffer from low throughput and
IEEE/ACM TRANSACTIONS ON NETWORKING, VOL. 16, NO. 3, JUNE 2008 497 XORs in the Air: Practical Wireless Network Coding Sachin Katti, Hariharan Rahul, Wenjun Hu, Dina Katabi, Muriel Médard, Senior Member,
More informationXORs in The Air: Practical Wireless Network Coding
XORs in The Air: Practical Wireless Network Coding Sachin Katti Hariharan Rahul Wenjun Hu Dina Katabi Muriel Médard Jon Crowcroft MIT CSAIL Univ. of Cambridge ABSTRACT This paper proposes COPE, a new architecture
More informationANewRoutingProtocolinAdHocNetworks with Unidirectional Links
ANewRoutingProtocolinAdHocNetworks with Unidirectional Links Deepesh Man Shrestha and Young-Bae Ko Graduate School of Information & Communication, Ajou University, South Korea {deepesh, youngko}@ajou.ac.kr
More informationMULTICAST broadcast services (MBS) have become essential
IEEE/ACM TRANSACTIONS ON NETWORKING, VOL. 19, NO. 3, JUNE 2011 869 An Adaptive Network Coded Retransmission Scheme for Single-Hop Wireless Multicast Broadcast Services Sameh Sorour, Student Member, IEEE,
More informationSome Optimization Trade-offs in Wireless Network Coding
Some Optimization Trade-offs in Wireless Network Coding Yalin Evren Sagduyu and Anthony Ephremides Electrical and Computer Engineering Department and Institute for Systems Research University of Maryland,
More informationNetwork Coding Based Packets Queue Operation for Wireless Ad Hoc Networks
Network Coding Based Packets Queue Operation for Wireless Ad Hoc Networks Shee Eng Tan, Zhan Wei Siew, Khairul Anuar Mohamad, Ismail Saad, Kenneth Tze Kin Teo Modelling, Simulation & Computing Laboratory,
More informationNetwork Coding Aware Power Control in Wireless Networks
Network Coding Aware Power Control in Wireless Networks Kai Su, Dan Zhang, Narayan B Mandayam WINLAB, Rutgers University 67 Route South, North Brunswick, NJ 892 Email: {kais, bacholic, narayan}@winlabrutgersedu
More informationResearch on Transmission Based on Collaboration Coding in WSNs
Research on Transmission Based on Collaboration Coding in WSNs LV Xiao-xing, ZHANG Bai-hai School of Automation Beijing Institute of Technology Beijing 8, China lvxx@mail.btvu.org Journal of Digital Information
More informationEnergy Efficient Broadcasting Using Network Coding Aware Protocol in Wireless Ad hoc Network
Energy Efficient Broadcasting Using Network Coding Aware Protocol in Wireless Ad hoc Network 1 Shuai Wang 2 Athanasios Vasilakos 1 Hongbo Jiang 1 Xiaoqiang Ma 1 Wenyu Liu 1 Kai Peng 1 Bo Liu 1 Yan Dong
More informationWQM: Practical, Adaptive, and Lightweight Wireless Queue Management System
WQM: Practical, Adaptive, and Lightweight Wireless Queue Management System Basem Shihada Computer Science & Electrical Engineering CEMSE, KAUST University of Waterloo Seminar December 8 th, 2014 2 3 How
More informationMinimizing Energy Consumption for Cooperative Network and Diversity Coded Sensor Networks
Minimizing Energy Consumption for Cooperative Network and Diversity Coded Sensor Networks WTS 2014 April 9-11, 2014 Washington, DC Gabriel E. Arrobo and Richard D. Gitlin Department of Electrical Engineering
More informationThe Importance of Being Opportunistic: Practical Network Coding for Wireless Environments
The Importance of Being Opportunistic: Practical Network Coding for Wireless Environments Sachin Katti Dina Katabi Wenjun Hu Hariharan Rahul Muriel Médard {skatti@, dk@, wenjun@csail., rahul@csail., medard@}mit.edu
More informationATCS: An Adaptive TCP Coding Scheme for Satellite IP Networks
KSII TRANSACTIONS ON INTERNET AND INFORMATION SYSTEMS VOL. 5, NO. 5, May 2011 1013 Copyright @ 2011 KSII ATCS: An Adaptive TCP Coding Scheme for Satellite IP Networks Wei Dong 1, Junfeng Wang 1, Minhuan
More informationLow Complexity Opportunistic Decoder for Network Coding
Low Complexity Opportunistic Decoder for Network Coding Bei Yin, Michael Wu, Guohui Wang, and Joseph R. Cavallaro ECE Department, Rice University, 6100 Main St., Houston, TX 77005 Email: {by2, mbw2, wgh,
More informationPNC BASED DISTRIBUTED MAC PROTOCOL IN WIRELESS NETWORKS
PNC BASED DISTRIBUTED MAC PROTOCOL IN WIRELESS NETWORKS Gowdara Rajasekhar Gowda 1, Dr. B R Sujatha 2 1MTech (DECS) student, E&C Dept, Malnad College of Engineering, Karnataka, India. 2Associate professor,
More informationA Systematic Approach to Network Coding Problems using Conflict Graphs
A Systematic Approach to Network Coding Problems using Conflict Graphs Jay Kumar Sundararajan Laboratory for Information and Decision Systems Massachusetts Institute of Technology Cambridge, MA 02139,
More informationCS 268: Computer Networking. Taking Advantage of Broadcast
CS 268: Computer Networking L-12 Wireless Broadcast Taking Advantage of Broadcast Opportunistic forwarding Network coding Assigned reading XORs In The Air: Practical Wireless Network Coding ExOR: Opportunistic
More informationA Mobile Platform for Measurements in Dynamic Topology Wireless Networks
A Mobile Platform for Measurements in Dynamic Topology Wireless Networks E. Scuderi, R.E. Parrinello, D. Izal, G.P. Perrucci, F.H.P. Fitzek, S. Palazzo, and A. Molinaro Abstract Due to the wide spread
More informationPiggyCode: a MAC layer network coding scheme to improve TCP performance over wireless networks
PiggyCode: a MAC layer network coding scheme to improve TCP performance over wireless networks Luca Scalia, Fabio Soldo, Mario Gerla Dipartimento di Ingegneria Elettrica, Elettronica e delle Telecomunicazioni,
More informationUAMAC: Unidirectional-Link Aware MAC Protocol for Heterogeneous Ad Hoc Networks
UAMAC: Unidirectional-Link Aware MAC Protocol for Heterogeneous Ad Hoc Networks Sung-Hee Lee, Jong-Mu Choi, and Young-Bae Ko College of Information and Communication, Ajou University, South Korea shlee@dmc.ajou.ac.kr,
More informationIs Physical Layer Error Correction sufficient for Video Multicast over IEEE g Networks?
Is Physical Layer Error Correction sufficient for Video Multicast over IEEE 82.11g Networks? Özgü Alay, Thanasis Korakis, Yao Wang, and Shivendra Panwar Department of Electrical and Computer Engineering,
More informationPractical Network Coding in Sensor Networks: Quo Vadis?
Practical Network Coding in Sensor Networks: Quo Vadis? Thiemo Voigt 1, Utz Roedig 2, Olaf Landsiedel 3,4, Kasun Samarasinghe 1, Mahesh Bogadi Shankar Prasad 1 1 Swedish Institute of Computer Science (SICS),
More informationAalborg Universitet. Published in: Globecom. I E E E Conference and Exhibition. DOI (link to publication from Publisher): /GLOCOM.2011.
Aalborg Universitet On-the-fly Packet Error Recovery in a Cooperative Cluster of Mobile Devices Vingelmann, Peter; Heide, Janus; Pedersen, Morten Videbæk; Fitzek, Frank Hanns Paul Published in: Globecom.
More informationCE693: Adv. Computer Networking
CE693: Adv. Computer Networking L-10 Wireless Broadcast Fall 1390 Acknowledgments: Lecture slides are from the graduate level Computer Networks course thought by Srinivasan Seshan at CMU. When slides are
More informationWireless broadcast transmission scheme for reliable video-streaming service
Wireless broadcast transmission scheme for reliable video-streaming service MELISA JUNUZOVIĆ, KEMAL ALIČ, ALEŠ ŠVIGELJ Department of Communication Systems, Jozef Stefan Institute Jozef Stefan International
More informationEmbracing Wireless Interference: Analog Network Coding
Embracing Wireless Interference: Analog Network Coding By Sachin Katti, Shyamnath Gollakota, and Dina Katabi Shyamala Villupuram Sundararaman University of Freiburg shyamala.villupuram.sundararaman@venus.uni-freiburg.de
More informationJournal of Electronics and Communication Engineering & Technology (JECET)
Journal of Electronics and Communication Engineering & Technology (JECET) JECET I A E M E Journal of Electronics and Communication Engineering & Technology (JECET)ISSN ISSN 2347-4181 (Print) ISSN 2347-419X
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 informationTO DESIGN ENERGY EFFICIENT PROTOCOL BY FINDING BEST NEIGHBOUR FOR ZIGBEE PROTOCOL
TO DESIGN ENERGY EFFICIENT PROTOCOL BY FINDING BEST NEIGHBOUR FOR ZIGBEE PROTOCOL 1 Mr. Sujeet D. Gawande, Prof. Amit M. Sahu 2 1 M.E. Scholar, Department of Computer Science and Engineering, G.H.R.C.E.M.,
More informationSystematic Network Coding with the Aid of a Full-Duplex Relay
Systematic Network Coding with the Aid of a Full-Duplex Relay Giuliano Giacaglia, Xiaomeng Shi, inji Kim, Daniel E. Lucani, uriel édard Research Laboratory of Electronics, assachusetts Institute of Technology,
More informationNetwork Coding To Improve Performance of AODV Protocol in Wireless Ad-Hoc Network
Network Coding To Improve Performance of AODV Protocol in Wireless Ad-Hoc Network 1 Mr.Tushar Gawande Department of Electronics Engineering B. D. College of Engineering, Sewagram, Wardha, India. gawande.tushar@gmail.com
More informationRouting in Ad Hoc Wireless Networks PROF. MICHAEL TSAI / DR. KATE LIN 2014/05/14
Routing in Ad Hoc Wireless Networks PROF. MICHAEL TSAI / DR. KATE LIN 2014/05/14 Routing Algorithms Link- State algorithm Each node maintains a view of the whole network topology Find the shortest path
More informationImplementation of Random Linear Network Coding using NVIDIA's CUDA toolkit
Implementation of Random Linear Network Coding using NVIDIA's CUDA toolkit Péter Vingelmann* and Frank H. P. Fitzek * Budapest University of Technology and Economics Aalborg University, Department of Electronic
More informationData Dissemination in the Wild A Testbed for High-Mobility MANETs Vingelmann, Peter; Pedersen, Morten Videbæk; Heide, Janus; Zhang, Qi; Fitzek, Frank
Downloaded from vbn.aau.dk on: April 18, 219 Aalborg Universitet Data Dissemination in the Wild A Testbed for High-Mobility MANETs Vingelmann, Peter; Pedersen, Morten Videbæk; Heide, Janus; Zhang, Qi;
More informationCoded Cooperative Data Exchange for Multiple Unicasts
Coded Cooperative Data Exchange for Multiple Unicasts Shahriar Etemadi Tajbakhsh and Parastoo Sadeghi Research School of Engineering The Australian National University Canberra, 000, Australia Emails:
More informationXCOR: Synergistic Inter flow Network Coding and Opportunistic Routing
Dimitrios Koutsonikolas (dkoutson@purdue.edu) Advisor: Y. Charlie Hu School of ECE, Purdue University XCOR: Synergistic Inter flow Network Coding and Opportunistic Routing 1. Abstract Opportunistic routing
More informationEnergy Consumption in Wireless Mesh Networks. Ulrik Wilken Rasmussen Aalborg University
Energy Consumption in Wireless Mesh Networks Ulrik Wilken Rasmussen Aalborg University The Faculties of Engineering, Science and Medicine Department of Electronic Systems Frederik Bajers Vej 7 Phone:
More informationKeywords: Medium access control, network coding, routing, throughput, transmission rate. I. INTRODUCTION
Performance Analysis of Network Parameters, Throughput Optimization Using Joint Routing, XOR Routing and Medium Access Control in Wireless Multihop Network 1 Dr. Anuradha M. S., 2 Ms. Anjali kulkarni 1
More informationAODV-PA: AODV with Path Accumulation
-PA: with Path Accumulation Sumit Gwalani Elizabeth M. Belding-Royer Department of Computer Science University of California, Santa Barbara fsumitg, ebeldingg@cs.ucsb.edu Charles E. Perkins Communications
More informationA Fast and Reliable Tree based Proactive Source Routing in Mobile Adhoc Network 1 Haseena M. K., 2 Annes Philip.
www.ijecs.in International Journal Of Engineering And Computer Science ISSN:239-7242 Volume 4 Issue 7 July 205, Page No. 3422-3425 A Fast and Reliable Tree based Proactive Source Routing in Mobile Adhoc
More informationEnhanced Broadcasting and Code Assignment in Mobile Ad Hoc Networks
Enhanced Broadcasting and Code Assignment in Mobile Ad Hoc Networks Jinfang Zhang, Zbigniew Dziong, Francois Gagnon and Michel Kadoch Department of Electrical Engineering, Ecole de Technologie Superieure
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 informationA Proactive Network Coding Strategy for Pervasive Wireless Networking
A Proactive Network Coding Strategy for Pervasive Wireless Networking Elena Fasolo, Michele Rossi,Jörg Widmer and Michele Zorzi DEI, University of Padova, via Gradenigo 6/B 353 Padova, Italy DoCoMo Euro-Labs,
More informationComputer Based Image Algorithm For Wireless Sensor Networks To Prevent Hotspot Locating Attack
Computer Based Image Algorithm For Wireless Sensor Networks To Prevent Hotspot Locating Attack J.Anbu selvan 1, P.Bharat 2, S.Mathiyalagan 3 J.Anand 4 1, 2, 3, 4 PG Scholar, BIT, Sathyamangalam ABSTRACT:
More informationolsr.org 'Optimized Link State Routing' and beyond December 28th, 2005 Elektra mesh.net
olsr.org 'Optimized Link State Routing' and December 28th, 2005 Elektra www.open mesh.net Introduction Olsr.org is aiming to an efficient opensource routing solution for wireless networks Work is currently
More informationExperiment and Evaluation of a Mobile Ad Hoc Network with AODV Routing Protocol
Experiment and Evaluation of a Mobile Ad Hoc Network with AODV Routing Protocol Kalyan Kalepu, Shiv Mehra and Chansu Yu, Department of Electrical and Computer Engineering Cleveland State University 2121
More informationNetwork Coding Approach: Intra-Cluster Information Exchange in Sensor Networks
1 Network oding pproach: Intra-luster Information Exchange in Sensor Networks Zhiqiang Xiong, Wei Liu, Jiaqing Huang, Wenqing heng, Zongkai Yang Huazhong University of Science and Technology Wuhan, Hubei
More informationTowards Reliable Broadcasting using ACKs
Towards Reliable Broadcasting using ACKs Mathilde Durvy Email: mathilde.durvy@epfl.ch Christina Fragouli Email: christina.fragouli@epfl.ch Patrick Thiran Email: patrick.thiran@epfl.ch Abstract We propose
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 informationLiterature Review on Characteristic Analysis of Efficient and Reliable Broadcast in Vehicular Networks
International Journal of Electronics and Communication Engineering. ISSN 0974-2166 Volume 6, Number 3 (2013), pp. 205-210 International Research Publication House http://www.irphouse.com Literature Review
More informationBounds on the Benefit of Network Coding: Throughput and Energy Saving in Wireless Networks
Bounds on the Benefit of Network Coding: Throughput and Energy Saving in Wireless Networks Alireza Keshavarz-Haddad Department of Electrical and Computer Engineering Rice University, 6100 Main Street,
More informationCongestion Control in Mobile Ad-Hoc Networks
Congestion Control in Mobile Ad-Hoc Networks 1 Sandeep Rana, 2 Varun Pundir, 3 Ram Sewak Singh, 4 Deepak Yadav 1, 2, 3, 4 Shanti Institute of Technology, Meerut Email: sandeepmietcs@gmail.com Email: varunpundir@hotmail.com
More informationWITH the evolution and popularity of wireless devices,
Network Coding with Wait Time Insertion and Configuration for TCP Communication in Wireless Multi-hop Networks Eiji Takimoto, Shuhei Aketa, Shoichi Saito, and Koichi Mouri Abstract In TCP communication
More informationError-Sensitive Adaptive Frame Aggregation in n WLANs
Error-Sensitive Adaptive Frame Aggregation in 802.11n WLANs Melody Moh, Teng Moh, and Ken Chan Department of Computer Science San Jose State University San Jose, CA, USA Outline 1. Introduction 2. Background
More informationInsecure Provable Secure Network Coding
Insecure Provable Secure Network Coding Yongge Wang UNC Charlotte, USA yonwang@uncc.edu October 18, 2009 Abstract Network coding allows the routers to mix the received information before forwarding them
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 informationand coverage as the nodes can act both as clients and routers. In this paper, the clients are distributed using four different
ISSN: 0975-766X CODEN: IJPTFI Available Online through Research Article www.ijptonline.com PERFORMANCE ANALYSIS FOR WIRELESS MESH NETWORK CONSIDERING DIFFERENT CLIENT DISTRIBUTION PATTERNS S.Dhivya #1,
More informationSupporting Service Differentiation for Real-Time and Best-Effort Traffic in Stateless Wireless Ad-Hoc Networks (SWAN)
Supporting Service Differentiation for Real-Time and Best-Effort Traffic in Stateless Wireless Ad-Hoc Networks (SWAN) G. S. Ahn, A. T. Campbell, A. Veres, and L. H. Sun IEEE Trans. On Mobile Computing
More informationJoint Routing, Scheduling, and Network Coding for Wireless Multihop Networks
211 International Symposium of Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks Joint Routing, Scheduling, and Network Coding for Wireless Multihop Networks Samat Shabdanov, Catherine
More informationImproved Joint Network-Channel Coding for the Multiple-Access Relay Channel
2012 7th International ICST Conference on Communications and Networking in China (CHINACOM) Improved Joint Network-Channel Coding for the Multiple-Access Relay Channel Wei Fang, Chunjing Hu, Zhuo Sun,
More informationMultipath TCP with Network Coding for Wireless Mesh Networks
This full text paper was peer reviewed at the direction of IEEE Communications Society subject matter experts for publication in the IEEE ICC 2 proceedings Multipath TCP with Network Coding for Wireless
More informationPerformance Analysis of the Intertwined Effects between Network Layers for g Transmissions
Performance Analysis of the Intertwined Effects between Network Layers for 802.11g Transmissions Jon Gretarsson, Feng Li, Mingzhe Li, Ashish Samant, Huahui Wu, Mark Claypool and Robert Kinicki WPI Computer
More informationCollisions & Virtual collisions in IEEE networks
Collisions & Virtual collisions in IEEE 82.11 networks Libin Jiang EE228a project report, Spring 26 Abstract Packet collisions lead to performance degradation in IEEE 82.11 [1] networks. The carrier-sensing
More informationPerformance of Multicast Traffic Coordinator Framework for Bandwidth Management of Real-Time Multimedia over Intranets
Performance of Coordinator Framework for Bandwidth Management of Real-Time Multimedia over Intranets Chin Hooi Tang, and Tat Chee Wan, Member, IEEE ComSoc. Abstract Quality of Service (QoS) schemes such
More informationQuality of Service Mechanism for MANET using Linux Semra Gulder, Mathieu Déziel
Quality of Service Mechanism for MANET using Linux Semra Gulder, Mathieu Déziel Semra.gulder@crc.ca, mathieu.deziel@crc.ca Abstract: This paper describes a QoS mechanism suitable for Mobile Ad Hoc Networks
More informationKeywords-ad-hoc networks; exploration and learning; routing protocols. ICN 2012 : The Eleventh International Conference on Networks
MANET with the Q-Routing Protocol Ramzi A. Haraty and Badieh Traboulsi Department of Computer Science and Mathematics Lebanese American University Beirut, Lebanon Email: rharaty@lau.edu.lb, badieh.taboulsi@lau.edu.lb
More informationCAR: Coding-Aware Opportunistic Routing in Wireless Mesh Networks
: Coding-Aware Opportunistic Routing in Wireless Mesh Networks Hongquan Liu and Yuantao Gu Received Jan., 3 Abstract An intermediate node in inter-flow network coding scheme, such as, needs to know exactly
More informationJoint Scheduling and Instantaneously Decodable Network Coding
1 Joint Scheduling and Instantaneously Decodable Network Coding Danail Traskov, Muriel Médard, Parastoo Sadeghi, and Ralf Koetter Institute for Communications Engineering, Technical University Munich,
More informationReal-time and Reliable Video Transport Protocol (RRVTP) for Visual Wireless Sensor Networks (VSNs)
Real-time and Reliable Video Transport Protocol (RRVTP) for Visual Wireless Sensor Networks (VSNs) Dr. Mohammed Ahmed Abdala, Mustafa Hussein Jabbar College of Information Engineering, Al-Nahrain University,
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 informationRD-TCP: Reorder Detecting TCP
RD-TCP: Reorder Detecting TCP Arjuna Sathiaseelan and Tomasz Radzik Department of Computer Science, King s College London, Strand, London WC2R 2LS {arjuna,radzik}@dcs.kcl.ac.uk Abstract. Numerous studies
More informationA Proposal for Network Coding with the IEEE Standard
A Proposal for Network Coding with the IEEE 802.15.6 Standard The MIT Faculty has made this article openly available. Please share how this access benefits you. Your story matters. Citation As Published
More informationA Joint Network-Channel Coding Technique for Single-Hop Wireless Networks
A Joint Network-Channel Coding Technique for Single-Hop Wireless Networks Tuan Tran, Thinh Nguyen and Bella Bose School of EECS, Oregon State University Corvallis, OR 97, USA {trantu, thinhq}@eecs.oregonstate.edu;
More informationPerformance Evaluation of Various Routing Protocols in MANET
208 Performance Evaluation of Various Routing Protocols in MANET Jaya Jacob 1,V.Seethalakshmi 2 1 II MECS,Sri Shakthi Institute of Science and Technology, Coimbatore, India 2 Associate Professor-ECE, Sri
More informationFigure 1: Ad-Hoc routing protocols.
Performance Analysis of Routing Protocols for Wireless Ad-Hoc Networks Sukhchandan Lally and Ljiljana Trajković Simon Fraser University Vancouver, British Columbia Canada E-mail: {lally, ljilja}@sfu.ca
More informationOn the Design of QoS aware Multicast Algorithms for Wireless Mesh Network. By Liang Zhao Director of Study: Dr. Ahmed Al-Dubai (CDCS)
On the Design of QoS aware Multicast Algorithms for Wireless Mesh Network By Liang Zhao Director of Study: Dr. Ahmed Al-Dubai (CDCS) Outline 1. Introduction to Wireless Mesh Networks 2. Multicast and its
More information