A Secure Time Synchronization Protocol for Mobile Underwater Wireless Sensor Network

Transcription

1 A Secure Time Synchronization Protocol for Mobile Underwater Wireless Sensor Network Reshma J Kunnuthara PG Student Dept ECE MBITS,Nellimattom India reshmajkunnuthara@gmail.com Abstract This paper presents a Cluster formation that ensures the security of synchronization under harsh underwater environments. Secure time synchronization is one of the key concerns for Underwater Wireless Sensor Networks (UWSNs). An energy-efficient communication algorithm LEACH, has been introduced which employs a hierarchical clustering done based on information received by the BS. In a clustered based hierarchical network, cluster heads are selected and it can be used to process and send the information while the sensor nodes are used to sense the data. The time synchronization process of Cluster formation include authentication,and intercluster synchronization phase. During the authentication phase, cluster heads are authenticated to beacons and ordinary nodes are authenticated to cluster heads. Intercluster synchronization phases, can be executed concurrently for reducing the number of messages generated in synchronization. This can also reduce synchronization errors as well as the number of synchronization messages than traditional protocols even when the network is attacked by malicious nodes. This algorithm will prolong the network life time by lowering the energy consumption. Index Terms LEACH, Cluster formation, Intercluster synchronization I. INTRODUCTION The largely unexplored vastness of the ocean, covering about two-thirds of the surface of Earth, has fascinated humans for as long as we have records. Its currents, chemical composition, and ecosystems are all highly variable as a function of space and time. Recently, there has been a growing interest in monitoring the marine environment for scientific exploration, commercial exploitation and coastline protection. The ideal vehicle for this type of extensive monitoring is a networked underwater wireless sensor distributed system, referred to as Underwater Wireless Sensor Network (UWSN).However, due to the high attenuation of radio waves in water, acoustic Communication is emerging as the most suitable media. Several characteristics specific to underwater acoustic communications and net working introduce additional design complexity into almost every layer of the network protocol stack. For example, low communication bandwidth, long propagation delays, higher error probability, and sensor node mobility are concerns that must be confronted. To make these application viable, there is a need to enable under water communication among underwater sensor nodes and vehicle must posses self configuration, location and movement information to relay monitored data to relay monitored to an on shore station. A synchronization algorithm for UWSNs must consider additional factors such as long propagation delays from the use of acoustic communication and sensor node mobility.these unique challenges make the accuracy of synchronization procedures for UWSNs even more critical. This Cluster based Time synchronization solutions specifically designed for UWSNs are needed to satisfy these new requirements. UWSNs are often deployed in an inaccessible and hostile environment, those unattended sensor nodes are likely to incur many critical security attacks. Time synchronization attacks have great effects on the set of sensor network applications and services since they heavily rely on accurate time synchronization to perform their neighbor s clocks are at a different time than they actually are. Time synchronization attacks have great effects on a set of sensor network applications and services since they heavily rely on accurate time synchronization to perform their respective functions. Secure time synchronization is one of the key concerns for Underwater Wireless Sensor Networks (UWSNs). This paper presents a Secure Synchronization protocol that ensures the security of synchronization under harsh underwater environments against various attacks. This algorithm distinguishes the propagation delay of downlink from that of uplink caused by node movement in order to improve time synchronization accuracy. This will also help in reducing the number of messages generated in synchronization. This algorithm will

2 help in improving the rate of successful message delivary. This will also help in improving the network life time. The paper is organized as follows. In Section II provides brief background of the existing algorithm and its drawbacks. In Section III shows the proposed algorithm shows simulation results, and in Section IV shows simulation results and in Section V concludes the paper. III. PROPOSED METHOD A. NETWORK TOPOLOGY UWSN is composed of a large number of nodes uniformly scattered in monitoring fields.a underwater sensor network architecture as shown in Fig.1 II. EXISTING ALGORITHMS In the literature, there are various time synchronization protocols for distributed systems like terrestrial radio sensor networks. Mobi-sync: efficient time synchronization for mobile underwater sensor networks [2] a novel time synchronization scheme for mobile underwater sensor networks. Mobi-Sync distinguishes itself from various approaches for terrestrial WSN by considering spatial correlation among the mobility patterns of neighbouring UWSNs nodes. This enables Mobi-Sync to accurately estimate the long dynamic propagation delays. Simulation results show that Mobi-Sync outperforms existing schemes in both accuracy and low propagation delay. Flooding Time Synchronization Protocol (FTSP) [3] is designed for sniper localization. Therefore, it is required to achieve considerably high precision. As FTSP applies a flooding technique, it is robust in regards to network topology changes. The FTSP is not applicable to underwater sensor network mainly because it also assumes instant reception. Additionally, it requires hardware calibration, which is not a completely software solution. Secure Time Synchronization for Wireless Sensor Network [4] this algorithm, shows the need of secure time synchronization, problem related with synchronization, how secure time synchronization can be achieved on sink node with reduced energy consumption, quickness in effective manner. This scheme removes different threats on synchronization and makes system more robust. This provided centralized control in distributed wireless sensor network which reduces complexity of real time application of wireless sensor network. Time Synchronization for Highlatency Networks [TSHL] [5] scheme designed for highlatency networks, and addresses long propagation delays and energy consumption issues. In TSHL, both one- way and two-ways MAC-layer message exchange are employed, where one-way is to estimate the clock skew and two-ways is to calculate the clock offset. Fig.5.1. Underwater sensor network architecture Given a UWSN, the whole network is composed of three types of nodes: beacons, cluster heads, and ordinary nodes. Beacons have unlimited energy resources and perfect timing information. In a clustered based hierarchical wireless sensor network CHs can be used to process and send the information while the sensor nodes are used to sense the The advantage of using the clustering for time synchronization is that CH can prolong the battery life of the individual sensors and also the network lifetime.ch can reduce the rate of energy consumption by scheduling activities in the cluster. Clustering reduce the communication overhead for synchronization. In this regard, they provide the time reference for the sensors positioned underwater. Beacons communicate with cluster heads and ordinary nodes through acoustic links. Each cluster has and only has one cluster head. All ordinary nodes connect to their cluster head via single hop. Fig.1 shows the topology of a UWSN with 8 sensor nodes and one beacon. The beacon is placed on the water surface and is equipped with GPS to obtain UTC time. Each sensor node is assigned a unique identifier (ID). B. Cluster based synchronization protocol Clustering is an effective technique that can greatly contribute to lifetime, and energy efficiency in wireless sensor networks (WSNs). A sensor network can be made scalable by assembling the sensor nodes into groups i.e. clusters. Every cluster has a leader, often referred to as the cluster head (CH). An energy-efficient communication protocol LEACH, has been introduced which employs a hierarchical clustering done based on information received by the BS. The CH collects and aggregates information from

3 sensors in its own cluster and passes on information to the BS. In each round of the cluster formation, network needs to follow the following steps select cluster head transfer the aggregated data. Data is collected at the wireless sensor node, compressed, and transmitted to the BS. Since sensor nodes are energy constrained, it is inefficient for all the sensors to transmit the data directly to the BS. Data generated from neighboring sensors is often redundant and highly correlated. To overcome the issue data aggregation is performed. C. LEACH Algorithm Low Energy Adaptive Clustering Hierarchy (LEACH) is the first hierarchical, self-organizing, adaptive cluster-based routing protocol for wireless sensor networks which partitions the nodes into clusters. The cluster structure update constantly in operation and one updating process is called a round. LEACH is short for low energy adaptive clustering hierarchy. Using cluster-based structure, the protocol localizes data communication within each cluster to reduce the long distance wireless communication and reduce the amount of data transmission; above all, cluster head node is randomly selected in a cyclic manner. The energy load of the whole network is evenly distributed to each sensor node, balancing energy consumption and extending the network lifetime. The topology of LEACH protocol is shown in Fig.2 Fig.2 LEACH protocol LEACH implementation is a cyclical process where each cycle is divided into 1.Set up phase: Initially, when clusters are being created, each node decides whether or not to become a cluster-head for the current round. Choose a node among the eligible nodes to become cluster head but we also make sure that the nodes are separated with a minimum separation distance (if possible) from the other cluster head nodes. In the cluster head selection part, cluster heads are randomly chosen from a list of eligible nodes. To decide which nodes that is eligible, the average energy of the remaining nodes in the network is calculated. In order to spread the load evenly, only nodes with energy above the average energy are eligible. As long as it is possible, or as long as the desired number of cluster heads is not attained, we choose a node among the eligible nodes that is further away than the minimum separation distance from all other chosen cluster heads. If that is not possible, we chose another node among the eligible nodes to become cluster head. When all cluster heads have been chosen and separated, generally with at least the minimum separation distance, clusters are created the same way as in. Each node that has elected itself a cluster-head for the current round broadcasts an advertisement message to the rest of the nodes. For this cluster-head-advertisement phase, the cluster-heads use a CSMA MAC protocol, and all cluster-heads transmit their advertisement using the same transmit energy. The non-cluster-head nodes must keep their receivers on during this phase of set-up to hear the advertisements of all the cluster-head nodes. After this phase is complete, each non-cluster-head node decides the cluster to which it will belong for this round. This decision is based on the received signal strength of the advertisement. This advertisement message ADV containing the CH identifier and the value of the threshold using the protocol CSMA/CA to avoid the collision between the cluster head. As a reply to the ADV message, each node sent a joint message to CH to be its member. The distance between the node and CH is based on the signal strength of received ADV message. Stronger is the signal nearer is the sender node. 2. STEADY STATE PHASE: The process of transferring aggregated data or sensed data from all the sensor nodes to the sink or base station is done under steady state phase. During this phase, nodes in each cluster sends data based on the allocated transmission time to their local cluster heads. To reduce the energy dissipation, the receiver of all non-cluster head nodes would be turned off until the nodes defined allocated time. The duration of the steady state phase is longer than the duration of the set-up phase in order to minimize overhead.to complete the set-up phase, each node send a join-request message after they receive a broadcast from the elected cluster-heads using a nonpersistent CSMA MAC protocol. The cluster-head creates a TDMA as shown in the LEACH flow chart and finally the nodes forming each cluster wait for their schedule before transmission. The steady phase starts immediately after the set-up phase. The cluster-heads gather all data from their

4 respective cluster members and send the respected data to the base station. Fig. 3 shows a flow chart of leach algorithm. Fig. 3 flow chart of leach algorithm The process of cluster formation for a UWSN is described as in the following step-by-step instructions. Step1 Those nodes having energy more than average energy is selected as cluster head. Fig. 4 Execution of Step1of cluster formation Step2.Each cluster head will try to add its neigh boring nodes as ordinary nodes that belong to its cluster in order of their degrees from high to low.if a sensor node happens to be the neigh boring node of multiple cluster heads, it will be assigned to the cluster head with the smallest ID as an ordinary of that cluster. Fig. 5 A scenario after execution of Step2 Step 3. Repeat Step 1 and Step 2 until all sensor nodes have identities of either cluster heads or ordinary nodes. Step 5. Each sensor node performs cluster consistency checking. If it identifies malicious nodes, it removes them from the network and restarts the cluster formation process from Step 1 The cluster for node n u is denoted as C u ; then for each node, n v C v ; node n u C u & n u c v ; if c v = C u, then cluster consistency is satisfied else if there exists a node n w C u such that c w c u is called cluster inconsistency. Here after, all sensor nodes are assigned identities of either cluster heads or ordinary nodes. After cluster consistency checking, the process of cluster formation is completed. An attacker may participate in the process of cluster formation using malicious nodes. These malicious nodes can launch different attacks in order to introduce cluster inconsistency. However, as each sensor node has a unique ID, all unicast messages with other nodes and broadcast messages can be authenticated with public key based digital signatures exchanged between nodes can be authenticated with unique pair-wise keys shared. By such means, the process of cluster formation can be executed securely. D. TIME SYNCHRONIZATION PROTOCOL The time synchronization of CLUSS can be divided into three phases: authentication phase, and intracluster synchronization phase. During the authentication phase, all sensor nodes need to be authenticated to each other. Cluster heads are authenticated to beacons and ordinary nodes are authenticated to cluster heads. During the intercluster synchronization phase, leach protocol uses TDMA algorithm to be utilized over a multi-hop wireless network. Wireless

5 time synchronization is used for many different purposes including location, proximity, energy efficiency, and mobility to name a few. Thus the cluster heads synchronize themselves with beacons. During the intracluster synchronization phase also, ordinary nodes synchronize themselves with cluster heads by using leach algorithm. The basic idea of our synchronization protocol is simple but effective in realizing time synchronization even when the network is attacked by malicious nodes. To the best of our knowledge, this is the first work that describes secure synchronization protocol for underwater wireless sensor networks. Authentication between node After the process of cluster formation, all sensor nodes know ID and nonce information of their neighboring nodes. Attacks to WSNs may come from outsiders or insiders. In cryptographically protected networks, outsiders do not have credentials (e.g., keys or certificates) to show that they are members of the network, whereas insiders do. Insiders may not always be trustworthy, as they may have been compromised, or have stolen their credentials from some legitimate node in the network. The solution we propose here is meant to protect the network from attacks by outsiders only.however, a CH in this architecture needs to use a strong transmission with long-distance radio to communicate directly with the BS. Neighboring sensor nodes in the network can establish secure links and broadcast authentication. Malicious or compromised nodes can be detected and eliminated from the network. The proposed network is designed for incrementally deployed networks, and employs a key chain to validate sensor node certificates at each increment. Identifing malicious node Each sensor is assigned with a unique ID and a secret key before deployment. Both the ID and the key are known to the sink node. Sensor nodes are left unattended after deployment. They monitor events of interests and send the data reports to the sink. When an event happens in the network, it will be detected by multiple sensing nodes. We use a cluster-based multihop routing scheme since recent research showed that clustering techniques are energy efficient. After the process of cluster formation, all sensor nodes know ID and nonce information of their neighboring nodes. The compromised nodes may attempt to provide falsified clock values, which in turn make the clock adjustment deviate from its desired value. Firstly, cluster heads will be authenticated to beacons. Suppose that C is a cluster head with1-hop distance to a beacon B. For the purpose of authentication with the beacon B, the cluster head C generates its secret key SK c and signs its nonce N c with SK C, which then becomes SK c (N c). Moreover, the cluster head also generates a hash value HCB o =H ID C, ID B,N C and signs H C B 0 with SKC, which then becomes SIG SK c (H ID c, ID B,N C ). Both SK c(n C) and SIG SK c(h ID c, ID B,N C ) are sent to the beacon B. On the other hand, the beacon B attempts to decrypt SK c(n C) using C s public key PK C and get the original N C. Furthermore, the beaconb also attempts to de crypt SIG SK c(n C) H ID C, ID B,N C using C s public key PK C and get the original.hcb 0. After that, the beacon B generates a hash value HCB 1 =H ID C, ID B,N C and compares HCB 1 with HCB 0. If HCB 1 matches HCB 0, then the beacon B generates another hash value HBC 0 =H ID B, ID C,N B,N C and signs HBC 0 with its secret key SK B, which then becomes SIG SK B H ID B, ID C,N B,N C ). In addition, the beacon B also signs its nonce N B with SKB, which then becomes SK B(N B). In turn, the beacon B sends SK B(N B) and SIG SK B(H ID B, ID C,N B,N C ) to the cluster head C. After receiving SK B(N B) and SIG SK B(H ID B, ID C,N B,N C ), the cluster head C decrypts them using B s public key PK B and get the original HBC 0 and N B. Moreover, the cluster head C generates a hash value HBC 1=H ID B, ID C,N B,N C and compares HBC 1 with HBC 0. If HBC 1 matches HBC 0, then the authentication is successful; otherwise, the authentication is failed. Likewise, ordinary nodes can be authenticated to cluster heads. After the execution of authentication phase, all neighboring nodes are authenticated with each other and they can communicate with each other securely. Authentication using SHA 256 hash function An n-bit hash is a map from arbitrary length messages to n-bit hash values. An n bit cryptographic hash is an n-bit hash which is one-way1 and collision-resistant. Such functions are important cryptographic primitives used for such things as digital signatures and password protection. Current popular hashes produce hash values of length n = 128(MD4 and MD5) and n = 160 (SHA-1), and therefore can provide no more than 64 or 80 bits of security, respectively, against collision attacks. Since the goal of the new Advanced Encryption Standard (AES) is to, at its three cryp to variable sizes, 128, 192, and 256 bits of security, There is a need for companion hash algorithms which provide similar levels of enhanced security. SHA-256, described, is a 256-bit hash and is meant to provide 128 bits

6 of security against collision attacks.sha-512, is a 512-bit hash, and is meant to provide 256 bits of security against collision attacks. To obtain a 384 bit hash value (192-bits of security) will require truncating the SHA-512 SHA-256 operates in the manner of MD4, MD5, and SHA The message to be hashed is 1) padded with its length in such a way that the result is a multiple of 512 bits long, and then 2) parsed into 512-bit message blocks M(1);M(2);:::;M(N). 3) The message blocks are processed one at a time: Beginning with a Beginning with a initial hash value H(0), sequentially compute H(i) = H(i1) + CM(i)(H(i1)); where C is the SHA-256 compression function and + means word-wise mod 232 addition. H(N) is the hash of M. The SHA-256 compression function operates on a 512- bit message block and a 256- bit intermediate hash value. It is essentially a 256-bit block cipher algorithm which encrypts the intermediate hash value using the message block as key. Hence there are two main components to describe are the SHA-256 compression function, and the SHA-256 message schedule. We will use the following notation: xed initial hash value H(0), sequentially compute H(i) = H(i1) + CM(i)(H(i1)); where C is the SHA-256 compression function and + means word-wise mod 232 addition. Intracluster synchronization phase During the intracluster synchronization phase, ordinary nodes synchronize themselves with cluster heads. During this phase, nodes in each cluster sends data based on the allocated transmission time to their local cluster heads. To reduce the energy dissipation, the receiver of all noncluster head nodes would be turned off until the nodes defined allocated time. After receiving all the data from the nodes, the cluster head aggregates all the data sent from the member nodes into a single signal and transfers it to the base station. The duration of the steady state phase is longer than the duration of the set-up phase in order to minimize overhead. The cluster-heads creates a TDMA schedule by using the LEACH algorithm with respect to global time reference, Beacon. TDMA schedule prevents collision among the data messages and prevents the energy conservation in non cluster-head nodes. The cluster-head node transmit TDMA schedule to all the non cluster-head nodes.the nodes forming each cluster wait for their schedule before transmission. This TDMA schedule will tell each node when it can transmit. Thus the non cluster-head nodes is synchronized with respect to the cluster head. Thus the whole network is get synchronized. E. Merits of Cluster based Synchronization When an existing sensor node leaves the network due to battery outage, if this sensor node is not the cluster head of any cluster, then there is nothing to do. When a new sensor node joins the network, the system will execute the process of cluster formation and assign new cluster heads for the newly formed clusters if needed. Moreover, the network battery life is sufficiently long to avoid recharging or replacing node batteries frequently in harsh underwater environments. Hence, the topology of the network does not change frequently after initial deployment and the cost for cluster maintenance only has a trifling impact on the proposed method in a UWSN. This distinguishes the propagation delay of down- link from that of uplink caused by node movement in order to improve time synchronization accuracy. Moreover, part of these two phases can be executed concurrently for reducing the number of messages generated in synchronization. CLUSS can reduce synchronization errors as well as the number of synchronization messages than traditional protocols even when the network is attacked by malicious node. IV. SIMULATION RESULTS Fig. 4 Simulation result shows CLUSS is a Clusterbased Secure Synchronization protocol. Given a UWSN, the whole network is composed of three types of nodes: beacons, cluster heads, and ordinary nodes. Low Energy Adaptive Clustering Hierarchy (LEACH) proposed is the first hierarchical, self-organizing, adaptive cluster-based routing protocol for wireless sensor networks which partitions the nodes into clusters is used here. LEACH is a hierarchical protocol in which most nodes transmits the data to cluster heads, and the cluster heads aggregate and compress the data and forward it to the base station. Node first senses its target and then sends the relevant information to its cluster-head. Then the cluster head aggregates and compresses the information received from all the nodes and sends it to the base station. By using this algorithm will prolong the network lifetime by lowering the energy consumption. This will also help in improving the packet delay ratio. CLUSS can also reduce synchronization errors as well as the number of synchronization messages than traditional

7 protocols even when the network is attacked by malicious nodes destination nodes to the number of packets sent from the source nodes. The performance is better when packet deliver ratio is high ratio is high. a) mobi-sync:time synchronization b) secure time sync algorithm algorithm Fig. 5 PDR versus Time since sync Fig. 4 Simulation result After the cluster heads are selected, the cluster heads advertise to all sensor nodes in them network that they are the new cluster heads. Then, the other nodes organize themselves into local clusters by choosing the most appropriate cluster head (normally the closest cluster head). During the steady-state phase the cluster heads receive sensed data from cluster members, and transfer the aggregated data to the BS. To complete the set-up phase, each node send a join-request message after they receive a broadcast from the elected cluster-heads using a nonpersistent CSMA MAC protocol. The cluster-head creates a TDMA and finally the nodes forming each cluster wait for their schedule before transmission. The steady phase starts immediately after the set-up phase.the non-cluster-head nodes must keep their receivers on during this phase of setup to hear the advertisements of all the cluster-head nodes. After this phase is complete, each non-cluster-head node decides the cluster to which it will belong for this round. This decision is based on the received signal strength of the advertisement. Performance Evaluation Fig.5 shows a graph of the Packet delivery ratio(pdr) obtained in the proposed secure synchronization algorithm and the existing mobi-sync:time synchronization algorithm. The graph plot the Packet delivery ratio versus time. PDR is the ratio of number of packets received at the Here in the fig.5 (a) times passes packet delivery ratio start increases at 2µs and PDR value is 45 at 6µs. As the packet delivery ratio is high so here is a better performance. In fig. 5 (b) times passes packet delivery ratio start increases at the beginig itself and the value of PDR ratio is 70 at 3.5µs itself. Thus from the graph it is clear that PDR is better in the proposed method than the existing method. so this approach has a better performance.. Fig.6 shows a graph of the network life time obtained in the proposed secure synchronization algorithm with the existing mobi-sync:time synchronization algorithm. The graph plot the network life time versus number of nodes. Network lifetime can alternatively be defined as the time until the first node dies. Network lifetime is the time span from the deployment to the instant when the network is considered non functional. Lifetime is expressed in terms of seconds in this paper and for a single node it can be evaluated by the following equation: L=einitial/etotal where e initial is initial energy of a sensor node, e total is total energy spent in the process of data transmission. Thus from the graph it is clear that network life time is better in the proposed method than the existing method. so this approach will prolong the network life time

8 REFERENCES [1] I.F. Akyildiz, D. Pompili, and T. Melodia, Underwater Acoustic Sensor Networks: Research Challenges, Ad Hoc Networks, vol. 3, no. 3, pp , Mar G. P. R [2] J. Liu, Z. Zhou, Z. Peng, and J.-H. Cui, Mobi-sync: efficient time synchronization for mobile underwater sensor networks, in Proceedings of the 4th ACM international Workshop on Underwater Networks, pp. 1 5, a)mobi-sync:time synchronization b) Secure time sync algorithm algorithm Fig.6. Network life time versus number of nodes Here in the fig 6.(a) shows that as the number of node in the network is 30 the network life time is decreased to In fig.6(b) shows that as the number of node in the network is 30 the network life time is only decreased upto Thus from the graph it is clear that network life time is better in the proposed method than the existing method. so this approach will prolong the network life time. V. CONCLUSION This paper proposed a paper proposed a Clusterbased Synchronization protocol that ensures the security of synchronization under harsh underwater environments against various attacks CLUSS distinguishes the propagation delay of down- link from that of uplink caused by node movement in order to improve time synchronization accuracy. Moreover, part of these two phases can be executed concurrently for reducing the number of messages generated in synchronization. The Cluster-based Synchronization protocol can reduce synchronization errors as well as the number of synchronization messages than traditional protocols even when the network is attacked by malicious nodes. In future work, we will investigate the influence of MAC layer activities to the performance of time synchronization protocols, such as packet loss and retransmission. Moreover, we will analysis the adaptability of our protocol and evaluate its performance through real ocean experiments. [3] M. Mar oti, B. Kusy, G. Simon, and A. L edeczi, The flooding time synchronization protocol, in Proceedings of the 2nd International Conference on Embedded Networked Sensor Systems (SenSys 04), pp , November [4] A. S. Uluagac, R. A. Beyah, and J. A. Copeland, Secure sourcebased loose synchronization (SOBAS) for wireless sensor networks, IEEE Transactions on Parallel and Distributed Systems, vol. 24, no. 4, pp , [5] A. A. Syed and J. Heidemann, Time synchronization for high latency acoustic networks, in Proceedings of the 25th IEEE International Conference on Computer Communications (INFOCOM 06), pp. 1 6, April [6] N. Chirdchoo, W.-S. Soh, and K.C. Chua, Mu-Sync: A Time Synchronization Protocol for Underwater Mobile Networks, Proc. Third ACM Int l Workshop Underwater Networks (WuWNet 08), Sept [7] R. B. Manjula and S. M. Sunilkumar, Issues in underwater acoustic sensor networks, International Journal of Computer and Electrical Engineering, vol. 3, no. 1, pp