Heuristic Approach to Select Opportunistic Routing Forwarders (HASORF) to Enhance Throughput for Wireless Sensor Networks

Biological schemes provide useful resources for designing adaptive routing protocols for wireless sensor networks (WSNs). The key idea behind using bioinspired routing is to find the optimal path to the destination. Similarly, the idea of opportunistic routing (OR) is to find the least number of hops to deliver the data to the destination. Numerous routing schemes have been proposed in WSNs while targeting various performance goals, such as throughput, delay, and link quality. Recently, OR schemes have come onto the scene in comparison with the traditional routing algorithms. The performance of OR schemes, however, highly depends on the selection of forwarder nodes. In this paper, we consider a chain network topology, where nodes are separated by an equal distance. The throughput of the chain network is analyzed mathematically, and based on the analysis results, a heuristic algorithm is proposed to choose the forwarder nodes. We evaluate the performance of the proposed Heuristic Approach to Select Opportunistic Routing Forwarders (HASORF) by using the ns-2 simulator and compare it with previous schemes, such as random routing, Extremely Opportunistic Routing (ExOR), and Simple Opportunistic Adaptive Routing (SOAR). The empirical results show that our proposed scheme achieves the best performance among them

Opportunistic Hybrid Transport Protocol (OHTP) for Cognitive Radio Ad Hoc Sensor Networks

The inefficient assignment of spectrum for different communications purposes, plus technology enhancements and ever-increasing usage of wireless technology is causing spectrum scarcity. To address this issue, one of the proposed solutions in the literature is to access the spectrum dynamically or opportunistically. Therefore, the concept of cognitive radio appeared, which opens up a new research paradigm. There is extensive research on the physical, medium access control and network layers. The impact of the transport layer on the performance of cognitive radio ad hoc sensor networks is still unknown/unexplored. The Internet’s de facto transport protocol is not well suited to wireless networks because of its congestion control mechanism. We propose an opportunistic hybrid transport protocol for cognitive radio ad hoc sensor networks. We developed a new congestion control mechanism to differentiate true congestion from interruption loss. After such detection and differentiation, we propose methods to handle them opportunistically. There are several benefits to window- and rate-based protocols. To exploit the benefits of both in order to enhance overall system performance, we propose a hybrid transport protocol. We empirically calculate the optimal threshold value to switch between window- and rate-based mechanisms. We then compare our proposed transport protocol to Transmission Control Protocol (TCP)-friendly rate control, TCP-friendly rate control for cognitive radio, and TCP-friendly window-based control. We ran an extensive set of simulations in Network Simulator 2. The results indicate that the proposed transport protocol performs better than all the others

D-PFA: A Discrete Metaheuristic Method for Solving Traveling Salesman Problem Using Pathfinder Algorithm

The Traveling Salesman Problem (TSP) which is a theoretical computer science and operations research problem, has several applications even in its purest formulation, such as the manufacture of microchips, planning, and logistics. There are many methods proposed in the literature to solve TSP with gains and losses. We propose a discrete metaheuristic method called D-PFA to solve this problem more efficiently. Initially, the Pathfinder Algorithm (PFA) was presented to handle issues involving continuous optimization, where it worked effectively. In recent years, there have been various published variants of PFA, and it has been frequently employed to address engineering challenges. In this study, the original PFA algorithm is broken into four sub-algorithms and every sub-algorithm is discretized and coupled to form a new algorithm. The proposed algorithm has a high degree of flexibility, a quick response time, strong exploration and exploitation. To validate the significant advantages of the proposed D-PFA, 34 different instances with different sizes are used in simulation results. The proposed method was also compared with 12 State-of-the-Art algorithms. Results indicate that the suggested approach is more competitive and resilient in solving TSP than other algorithms in different aspects. A conclusion and an outlook on future studies and applications are given at the end of the paper