Coverage Protocols for Wireless Sensor Networks: Review and Future Directions

The coverage problem in wireless sensor networks (WSNs) can be generally defined as a measure of how effectively a network field is monitored by its sensor nodes. This problem has attracted a lot of interest over the years and as a result, many coverage protocols were proposed. In this survey, we first propose a taxonomy for classifying coverage protocols in WSNs. Then, we classify the coverage protocols into three categories (i.e. coverage aware deployment protocols, sleep scheduling protocols for flat networks, and cluster-based sleep scheduling protocols) based on the network stage where the coverage is optimized. For each category, relevant protocols are thoroughly reviewed and classified based on the adopted coverage techniques. Finally, we discuss open issues (and recommend future directions to resolve them) associated with the design of realistic coverage protocols. Issues such as realistic sensing models, realistic energy consumption models, realistic connectivity models and sensor localization are covered

Multihop clustering algorithm for load balancing in wireless sensor networks

The paper presents a new cluster based routing algorithm that exploits the redundancy properties of the sensor networks in order to address the traditional problem of load balancing and energy efficiency in the WSNs.The algorithm makes use of the nodes in a sensor network of which area coverage is covered by the neighbours of the nodes and mark them as temporary cluster heads. The algorithm then forms two layers of multi hop communication. The bottom layer which involves intra cluster communication and the top layer which involves inter cluster communication involving the temporary cluster heads. Performance studies indicate that the proposed algorithm solves effectively the problem of load balancing and is also more efficient in terms of energy consumption from Leach and the enhanced version of Leach

Adjacency Matrix Based Energy Efficient Scheduling using S-MAC Protocol in Wireless Sensor Networks

Communication is the main motive in any Networks whether it is Wireless Sensor Network, Ad-Hoc networks, Mobile Networks, Wired Networks, Local Area Network, Metropolitan Area Network, Wireless Area Network etc, hence it must be energy efficient. The main parameters for energy efficient communication are maximizing network lifetime, saving energy at the different nodes, sending the packets in minimum time delay, higher throughput etc. This paper focuses mainly on the energy efficient communication with the help of Adjacency Matrix in the Wireless Sensor Networks. The energy efficient scheduling can be done by putting the idle node in to sleep node so energy at the idle node can be saved. The proposed model in this paper first forms the adjacency matrix and broadcasts the information about the total number of existing nodes with depths to the other nodes in the same cluster from controller node. When every node receives the node information about the other nodes for same cluster they communicate based on the shortest depths and schedules the idle node in to sleep mode for a specific time threshold so energy at the idle nodes can be saved.Comment: 20 pages, 2 figures, 14 tables, 5 equations, International Journal of Computer Networks & Communications (IJCNC),March 2012, Volume 4, No. 2, March 201

Multihop clustering algorithm for load balancing in wireless sensor networks

The paper presents a new cluster based routing algorithm that exploits the redundancy properties of the sensor networks in order to address the traditional problem of load balancing and energy efficiency in the WSNs.The algorithm makes use of the nodes in a sensor network of which area coverage is covered by the neighbours of the nodes and mark them as temporary cluster heads. The algorithm then forms two layers of multi hop communication. The bottom layer which involves intra cluster communication and the top layer which involves inter cluster communication involving the temporary cluster heads. Performance studies indicate that the proposed algorithm solves effectively the problem of load balancing and is also more efficient in terms of energy consumption from Leach and the enhanced version of Leach

A Coverage Monitoring algorithm based on Learning Automata for Wireless Sensor Networks

To cover a set of targets with known locations within an area with limited or prohibited ground access using a wireless sensor network, one approach is to deploy the sensors remotely, from an aircraft. In this approach, the lack of precise sensor placement is compensated by redundant de-ployment of sensor nodes. This redundancy can also be used for extending the lifetime of the network, if a proper scheduling mechanism is available for scheduling the active and sleep times of sensor nodes in such a way that each node is in active mode only if it is required to. In this pa-per, we propose an efficient scheduling method based on learning automata and we called it LAML, in which each node is equipped with a learning automaton, which helps the node to select its proper state (active or sleep), at any given time. To study the performance of the proposed method, computer simulations are conducted. Results of these simulations show that the pro-posed scheduling method can better prolong the lifetime of the network in comparison to similar existing method

The Design of Medium Access Control (MAC) Protocols for Energy Efficient and QoS Provision in Wireless Sensor Networks

This thesis work focuses on innovative design of media access control (MAC) protocols in wireless sensor networks (WNSs). The characteristics of the WSN inquire that the network service design considers both energy efficiency and the associated application requirement. However, most existing protocols address only the issue of energy efficiency. In this thesis, a MAC protocol has been proposed (referred to as Q-MAC) that not only minimized the energy consumption in multi-hop WSNs, but also provides Quality of Service (QoS) by differentiating network services based on priority levels prescribed by different applications. The priority levels reflect the state of system resources including residual energy and queue occupancies. Q-MAC contains both intra- and inter- node arbitration mechanisms. The intra-node packet scheduling employs a multiple queuing architectures, and applies a scheduling scheme consisting of packet classification and weighted arbitration. We introduce the Power Conservation MACAW (PC-MACAW), a power-aware scheduling mechanism which, together with the Loosely Prioritized Random Access (LPRA) algorithm, govern the inter-node scheduling. Performance evaluation are conducted between Q-MAC and S-MAC with respect to two performance metrics: energy consumption and average latency. Simulation results indicate Q-MAC achieves comparable performance to that of S-MAC in non-prioritized traffic scenarios. When packets with different priorities are introduced, Q-MAC yields noticeable average latency differentiations between the classes of service, while preserving the same degree of energy consumption as that of S-MAC. Since the high density nature of WSN may introduce heavy traffic load and thus consume large amount of energy for communication, another MAC protocol, referred to as the Deployment-oriented MAC (D-MAC)has been further proposed. D-MAC minimalizes both sensing and communication redundancy by putting majority of redundant nodes into the sleep state. The idea is to establish a sensing and communication backbone covering the whole sensing field with the least sensing and communication redundancy. In specific, we use equal-size rectangular cells to partition the sensing field and chose the size of each cell in a way such that regardless of the actual location within the cell, a node can always sense the whole cell and communicate with all the nodes in neighboring cells. Once the sensing field has been partitioned using these cells, a localized Location-aware Selection Algorithm (LSA) is carried out to pick up only one node within each cell to be active for a fixed amount of period. This selection is energy-oriented, only nodes with a maximum energy will be on and the rest of nodes will be put into the sleep state once the selection process is over. To balance the energy consumption, the selection algorithm is periodically conducted until all the nodes are out of power. Simulation results indicated that D-MAC saves around 80% energy compared to that of S-MAC and Q-MAC, while maintaining 99% coverage. D-MAC is also superior to S-MAC and Q-MAC in terms of average latency. However, the use of GPS in D-MAC in identifying the nodes within the same cell, would cause extra cost and complexity for the design of sensor nodes

Selecting source image sensor nodes based on 2-hop information to improve image transmissions to mobile robot sinks in search \& rescue operations

We consider Robot-assisted Search $\&$ Rescue operations enhanced with some fixed image sensor nodes capable of capturing and sending visual information to a robot sink. In order to increase the performance of image transfer from image sensor nodes to the robot sinks we propose a 2-hop neighborhood information-based cover set selection to determine the most relevant image sensor nodes to activate. Then, in order to be consistent with our proposed approach, a multi-path extension of Greedy Perimeter Stateless Routing (called T-GPSR) wherein routing decisions are also based on 2-hop neighborhood information is proposed. Simulation results show that our proposal reduces packet losses, enabling fast packet delivery and higher visual quality of received images at the robot sink