Mathematically Engineered Adams Optimizer for Energy Efficient and Optimal Routing Approach for the Wireless Sensor Network

Wireless Sensor Network (WSN) comprises numerous Sensor Nodes (SN) scattered across a network to observe the atmospheric condition where the SN is the minimum cost. Vast usage of energy during data transmission is the primary design issue in WSNs that can be addressed by routing and clustering techniques. WSN has diverse transmission paths with unstable nodes, where the energy consumption is high, and the Quality of Service (QoS) is affected. The high data transmission delay and inefficient throughput indicate the ineffectiveness of WSN. To overcome this issue, this research concentrates on energy-efficient optimal routing formulated with the assistance of a mathematical approach and Adams optimizer. The mathematics’ based Pareto optimization is utilized to optimize the Adam Moment Estimation (Adam) that trains Deep Learning (DL) network that is deployed in both heterogeneous and homogeneous networks. The learning process is enhanced with the support of Pareto optimization, and the multi-objective problem is efficiently handled. In this context, Pareto optimization balances the path construction, and the equitable distribution issue is rectified by the Adams-based DL network. The proposed Pareto-integrated Adams Optimizer for Energy Efficient Routing (PAOEER) sustains the WSN performance by enhancing network parameters. The PAOEER achieves a higher Packet Delivery Ratio (PDR) of 97.18% and minimal Energy Consumption (EC) of 112.34 J. The simulation analysis shows that the proposed PAOEER is effective and outperforms the existing state-of-the-art techniques, indicating PAOEER is a promising alternative

Data Gathering with Tour Length-Constrained

In this paper, given a single mobile element and a time deadline, we investigate the problem of designing the mobile element tour to visit subset of nodes, such that the length of this tour is bounded by the time deadline and the communication cost between nodes outside and inside the tour is minimized. The nodes that the mobile element tour visits, works as cache points that store the data of the other nodes. Several algorithms in the literature have tackled this problem by separating two phases; the construction of the mobile element tour from the computation of the forwarding trees to the cache points. In this paper, we propose algorithmic solutions that alternate between these phases and iteratively improves the outcome of each phase based on the result of the other. We compare the resulting performance of our solutions with that of previous work

Data Gathering with Tour Length-Constrained

In this paper, given a single mobile element and a time deadline, we investigate the problem of designing the mobile element tour to visit subset of nodes, such that the length of this tour is bounded by the time deadline and the communication cost between nodes outside and inside the tour is minimized. The nodes that the mobile element tour visits, works as cache points that store the data of the other nodes. Several algorithms in the literature have tackled this problem by separating two phases; the construction of the mobile element tour from the computation of the forwarding trees to the cache points. In this paper, we propose algorithmic solutions that alternate between these phases and iteratively improves the outcome of each phase based on the result of the other. We compare the resulting performance of our solutions with that of previous work

A New Random Walk for Replica Detection in WSNs

The authors wish to thanks the anonymous reviewers for their valuable comments for the improvement of this manuscript. The authors wish to acknowledge the support and help of Deanship of Scientific Research at Jazan University and the authors also extend their sincere appreciations to Deanship of Scientific Research at King Saud University for its funding this Prolific Research Group (PRG-1436-16).Wireless Sensor Networks (WSNs) are vulnerable to Node Replication attacks or Clone attacks. Among all the existing clone detection protocols in WSNs, RAWL shows the most promising results by employing Simple Random Walk (SRW). More recently, RAND outperforms RAWL by incorporating Network Division with SRW. Both RAND and RAWL have used SRW for random selection of witness nodes which is problematic because of frequently revisiting the previously passed nodes that leads to longer delays, high expenditures of energy with lower probability that witness nodes intersect. To circumvent this problem, we propose to employ a new kind of constrained random walk, namely Single Stage Memory Random Walk and present a distributed technique called SSRWND (Single Stage Memory Random Walk with Network Division). In SSRWND, single stage memory random walk is combined with network division aiming to decrease the communication and memory costs while keeping the detection probability higher. Through intensive simulations it is verified that SSRWND guarantees higher witness node security with moderate communication and memory overheads. SSRWND is expedient for security oriented application fields of WSNs like military and medical.Yeshttp://www.plosone.org/static/editorial#pee