Connected Target Coverage (CTC) problem [8], covering given targets fully with the deployed sensors and also guaranteeing connectivity to a sink node, is a challenging scheduling problem. In this paper, unlike the existing heuristic algorithms, we adopt the probabilistic coverage model to solve the problem and develop a heuristic algorithm called CWGC-PM (Communication Weighted Greedy Cover-Probabilistic Model) to extend the network lifetime while such coverage and connectivity constraints are satisfied. Simulation results are presented to evaluate the performance of the proposed algorithm and they show that the probabilistic coverage model can capture the diverse sensing characteristics of sensor nodes in the real world.
We propose a context-awareness routing algorithm—the DDV- (Dynamic Direction Vector-) hop algorithm—in mobile ad hoc networks. The existing algorithm in MANET has the limitations of the dynamic network topology and the absence of network expandability of the mobility of nodes. The proposed algorithm performs cluster formation for the base station using the range of direction and threshold of velocity. We calculate the exchange of the cluster head node probability using the direction and velocity for maintaining cluster formation. The DDV-hop algorithm, a probabilistic routing protocol for such networks, is proposed and then compared to the earlier presented algorithms through simulations. The simulations are conducted on a number of clusters, network areas, transmission ranges, and velocity of nodes in mobile networks. Our results suggest that the DDV-hop algorithm demonstrates efficiency of eventual delivery and maintains the proper number of clusters and cluster members regardless of topology changes with a lower communication overhead in several interesting environments.
Mobile ad hoc networks comprise mobile nodes. The nodes both send and receive messages and can communicate with each other. Thus, the network builds its own network structure that is not dependent on the infrastructure. Owing to the characteristics of mobile ad hoc networks, they have been used in environments of poor communication, such as those in which the infrastructure cannot be built; for example, disaster areas and war zones. In this article, we propose an advanced energy-conserving optimal path schedule algorithm. The proposed algorithm sets the routing path using the relative angle, which is the distance between the source node and the base station. Using simulation results, we compared the proposed algorithm to existing algorithms. The protocol used by the proposed algorithm provides a higher packet delivery ratio and lower energy consumption than the lowest ID clustering algorithm and the mobility-based metric for clustering in the mobile ad hoc network algorithm.
In this paper, we introduce a method that can be used to select the position of head node for context-awareness information. The validity of the head node optimal location is saving the energy in the path according to the clustering. It is important how to elect one of the relay node for energy efficiency routing. Existing LEACH algorithm to elect the head node when the node's energy probability distribution function based on the management of the head node is optional cycle. However, in this case, the distance of the relay node status information including context-awareness parameters does not reflect. These factors are not suitable for the relay node or nodes are included in the probability distribution during the head node selects occurs. In particular, to solve the problems from the LEACH-based hierarchical clustering algorithms, this study defines location with the status context information and the residual energy factor in choosing topology of the structure adjacent nodes. The proposed ECOPS (Energy Conserving Optimal path Schedule) algorithm that contextual information is contributed for head node selection in topology protocols. This proposed algorithm has the head node replacement situations from the candidate head node in the optimal path and efficient energy conservation that is the path of the member nodes. The new head node election technique show improving the entire node lifetime and network in management the network from simulation results.
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