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This paper illustrates how known methods and techniques for solving problems in the area of wired interconnection networks can be adapted to solve problems for wireless mobile networks. We make use of a known construction of disjoint paths in the k-ary n-cube interconnection network to design a reliable multipath routing protocol for mobile ad-hoc networks (MANETs). With the help of node positioning, node mobility is masked and the problem of routing between mobile nodes is transformed to a problem of routing between fixed cells of a logical 3-dimensional grid. Analytical performance evaluation results for the proposed protocol are obtained showing its high reliability. To the best of our knowledge, the proposed protocol is the first multipath source routing protocol for MANETs. We believe other wireless communication problems can be solved using a similar approach based on adapting solutions from wired interconnection networks.

Internet of Things (IoT) is a network of smart things. It indicates the ability that the mentioned physical things transfer information with each other. The characteristics of these networks, such as topology dynamicity and energy constraint, make the routing problem a challenging task in these networks. Traditional routing methods could not achieve the required performance in these networks. Therefore, developers of these networks have to consider specific routing methods in order to satisfy their requirements. One of the routing methods is utilization of the multipath protocols in which data are sent to its destination using multiple routes with separate links. One of such protocols is AOMDV routing protocol. In this paper, AOMDV is improved using gray system theory which chooses the best paths used for separate routes to send packets. To do this, Ad hoc On-demand Multipath Distance Vector (AOMDV) packet format is altered and some fields are added to it so that energy criteria, link expiration time, and signal-to-noise ratio can also be considered during selection of the best route. The proposed method named RMPGST-IoT is introduced which chooses the routes with highest rank for concurrent transmission of data, using a specific method based on the gray system theory. In order to evaluate the results, the proposed Routing Multipath based on Gray System Theory (RMPGST)-IoT method is compared to the Emergency Response IoT based on Global Information Decision (ERGID) and Ad hoc Delay-aware Distributed Routing Model (ADRM)-IoT approaches in terms of throughput, packet receiving rate, packet loss rate, average remaining energy, and network lifetime. The results demonstrate that the performance of the proposed RMPGST-IoT is superior to that of ERGID and ADRM-IoT approaches.

Internet of Things (IoT) plays a vital role in the world of Internet and integrates computing devices. The digital machines provide unique identifiers. The capacity to send data through the network using a better path is one of the capabilities of digital machines. IoT generates huge data based on fast aggregation data and processes these data efficiently. In this paper, a multi-objective hybrid woodpecker and flamingo search optimization algorithm is proposed for finding optimum Cluster Head (CH)-based energy-aware routing protocol in IoTs environment (Hyb-WFSOA-CHS-IoT). Here, the proposed Hyb-WFSOA-CHS-IoT model executes routing method through CH. The woodpecker and flamingo search optimization algorithm is used as the intelligent CH selection that consumes same energy as sensors. Hybrid woodpecker and flamingo search optimization algorithm (Hyb-WFSOA) is examined by using fitness functions, like distance, delay, energy consumption, throughput. The proposed Hyb-WFSOA-CHS-IoT method is activated in MATLAB software. Then, the performance of the proposed system is examined with different metrics, like delay, packet delivery ratio, throughput, network lifetime, energy consumption. Therefore, the proposed method attains lower delay 28.38%, 32.34% and 47.45%, higher delivery ratio 19.34%, 23.12% and 18.96% and lower energy consumption 11.25%, 7.90% and 12.88% compared with existing methods, like multi-objective fractional gravitational search algorithm for energy-efficient routing on IoT (FGSA-CHS-IoT), multi-objective sunflower-based gray wolf optimization algorithm for multiple path routing on IoT network (SFG-CHS-IoT) and energy-aware routing in the IoT with improved grasshopper metaheuristic algorithm with chaos theory and fuzzy Logic (FLGOA-CHS-IoT).

Mobile ad hoc network (MANET) consists of a group of self-operated mobile nodes that form a network without considering predefined infrastructure. In the network, each node poses less energy due to battery-operated sensor nodes. Numerous methods are devised for routing, but each method suffered from the energy constraint. This paper proposes an energy-efficient multipath routing protocol for exploiting different routes between source and destination to mitigate energy constraints. The key idea is to determine the optimal path from a set of paths available between the source and the target node. To improve the security in routing protocol, the factors, like energy, trust, and mobility are considered as major components. Here, the trust is modeled by considering trust factors, like average encounter rate (AER), successful cooperation frequency (SCF), direct trust, integrity factor, and forwarding rate factor. Moreover, secure routing is performed between the nodes using the proposed Adaptive-Atom Whale Optimization algorithm (Adaptive-AWOA). The proposed Adaptive-AWOA) is designed by incorporating the Adaptive concept in the Atom Whale Optimization algorithm (AWOA). The fitness function is newly modeled considering mobility, energy, and trust factors. The proposed Adaptive-AWOA outperformed the other methods with a minimal end-to-end delay of 0.009, maximal throughput of 85.802% and maximal packet delivery ratio (PDR) of 97.391%, respectively.

A cost-aware multipath routing algorithm is proposed to obtain multiple paths for mobile wireless sensor networks. The proposed algorithm simultaneously considers the real-time residual energy of nodes, the real-time queue length of nodes and the priorities of multimedia streams in routing decision. Compared with the MP-OLSR algorithm, simulation results show that the proposed algorithm evidently achieves better performance in terms of the balance of node energy consumption, the ratio of received packets, the end-to-end transmission delay and the delay jitter.