An enhancement of path selection to cluster head based on multi-hop routing in two-tier wireless sensor network

Wireless Sensor Network (WSN) is a distributed wireless connection that consists many wireless sensor devices. It is used to get information from the surrounding activities or the environment and send the details to the user for future work. Due to its advantages, WSN has been widely used to help people to collect, monitor and analyse data. However, the biggest limitation of WSN is about the network lifetime. Usually WSN has a small energy capacity for operation, and after the energy was used up below the threshold value, it will then be declared as a dead node. When this happens, the sensor node cannot receive and send the data until the energy is renewed. To reduce WSN energy consumption, the process of selecting a path to the destination is very important. Currently, the data transmission from sensor nodes to the cluster head uses a single hop which consumes more energy; thus, in this paper the enhancement of previous algorithm, which is MAP, the data transmission will use several paths to reach the cluster head. The best path uses a small amount of energy and will take a short time for packet delivery. The element of Shortest Path First (SPF) Algorithm that is used in a routing protocol will be implemented. It will determine the path based on a cost, in which the decision will be made depending on the lowest cost between several connected paths. By using the MATLAB simulation tool, the performance of SPF algorithm and conventional method will be evaluated. The expected result of SPF implementation will increase the energy consumption in order to prolong the network lifetime for WSN

Trust-based secure clustering in WSN-based intelligent transportation systems

Increasing the number of vehicles on roads leads to congestion and safety problems. Wireless Sensor Network (WSN) is a promising technology providing Intelligent Transportation Systems (ITS) to address these problems. Usually, WSN-based applications, including ITS ones, incur high communication overhead to support efficient connectivity and communication activities. In the ITS environment, clustering would help in addressing the high communication overhead problem. In this paper, we introduce a bio-inspired and trust-based cluster head selection approach for WSN adopted in ITS applications. A trust model is designed and used to compute a trust level for each node and the Bat Optimization Algorithm (BOA) is used to select the cluster heads based on three parameters: residual energy, trust value and the number of neighbors. The simulation results showed that our proposed model is energy efficient (i.e., its power consumption is more efficient than many well-known clustering algorithm such as LEACH, SEP, and DEEC under homogeneous and heterogeneous networks). In addition, the results demonstrated that our proposed model achieved longer network lifetime, i.e., nodes are kept alive longer than what LEACH, SEP and DEEC can achieve. Moreover, the the proposed model showed that the average trust value of selected Cluster Head (CH) is high under different percentage (30% and 50%) of malicious nodes

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

Distributed autonomy and trade-offs in online multiobject k-coverage

In this article, we explore the online multiobject k-coverage problem in visual sensor networks. This problem combines k-coverage and the cooperative multirobot observation of multiple moving targets problem, and thereby captures key features of rapidly deployed camera networks, including redundancy and team-based tracking of evasive or unpredictable targets. The benefits of using mobile cameras are demonstrated and we explore the balance of autonomy between cameras generating new subgoals, and those responders able to fulfill them. We show that higher performance against global goals is achieved when decisions are delegated to potential responders who treat subgoals as optional, rather than as obligations that override existing goals without question. This is because responders have up-to-date knowledge of their own state and progress toward goals where they are situated, which is typically old or incomplete at locations remote from them. Examining the extent to which approaches overprovision or underprovision coverage, we find that being well suited for achieving 1-coverage does not imply good performance at k-coverage. Depending on the structure of the environment, the problems of 1-coverage and k-coverage are not necessarily aligned and that there is often a trade-off to be made between standard coverage maximization and achieving k-coverage