Meta heuristics is an optimization approach that works as an intelligent technique to solve optimization problems. Evolutionary algorithms, human-based algorithms, physics-based algorithms and swarm intelligence are categorized under meta -heuristic algorithms. This study presents a critical review of meta -heuristic algorithms for future reference, including concepts, applications, advantages and disadvantages, before focusing on one specific meta -heuristic algorithm, namely, Emperor Penguin Optimizer (EPO). It is an intelligent algorithm developed after observing the behaviour of emperor penguins during cold winters. This technique was introduced by Dhiman in 2018 and adopted to solve optimization problems. The study reviews the algorithm variants starting from its invention in 2018 until 2022. The literature is comprehensively reviewed to reflect on the progress of the algorithm’s adoption, highlighting a new area for improvement. The most significant result is that the proposed algorithm has been proven an effective technique. The merits and demerits of the algorithm are explored to provide valuable perspectives for future research. This study answers the question regarding meta -heuristic algorithms’ effectiveness, especially EPO. Both beginners and experts of EPO research can use the findings of this study as guidelines for enhancing current concepts and applications of state-of-the-art algorithms for future development works. 

Emperor penguin optimizer: A comprehensive review based on state-of-the-art meta-heuristic algorithms

A Mobil Ad hoc Network (MANET) is a dynamic multi-hop infrastructure-less wireless network that comprises of a collection of mobile, self-organized, self-configured wireless nodes. A routing protocol in MANET is used to find routes between mobile nodes to facilitate communication within the network. Numerous routing protocols have been proposed for MANET. Those routing protocols are designed to adaptively accommodate for dynamic unpredictable changes in network's topology. MANET characteristics such as openness, restricted resources and decentralization impact node's efficiency and made it easy to be affected by various security attacks, especially the Distributed Denial of Service (DDoS) attacks. These DDoS attacks consume all system resources like battery power, bandwidth, energy, CPU, and render those resources and nodes unavailable to the legitimate users. The aim of this research is to implement a simulation model called Distributed Denial of Service Simulation Model (DDoS-Sim) to examine the effect of DDoS attack on various routing protocols in MANETs namely: Ad hoc On-Demand Distance Vector (AODV), Dynamic Source Routing (DSR) and Destination-Sequenced Distance-Vector (DSDV). These routing protocols follow the reactive and proactive routing algorithms. The introduced model uses the network simulator 2 (NS-2) to apply DDoS on the three selected routing protocols. The performance of routings protocols was analyzed under the consequences of the attack in terms of packet delivery fraction and end-to-end delay. 

Performance Analysis of the Impact of DDoS Attack on Routing Protocols in Infrastructure-less Mobile Networks

Mobility prediction for random walk mobility model using ARIMA in mobile ad hoc networks

An energy-efficient MANET relay node selection and routing using a fuzzy-based analytic hierarchy process

Opportunities networks’ message transmission is significantly impacted by routing prediction, which has been a focus of opportunity network research. The network of student nodes with smart devices is a particular type of opportunity network in the campus setting, and the predictability of campus node movement trajectories is also influenced by the regularity of students’ social mobility. In this research, a novel Markov route prediction method is proposed under the campus background. When two nodes meet, they share the movement track data of other nodes stored in each other’s cache in order to predict the probability of two nodes meeting in the future. The impact of the node within the group is indicated by the node centrality. The utility value of the message is defined to describe the spread degree of the message and the energy consumption of the current node, then the cache is managed according to the utility value. By creating a concurrent hash mapping table of delivered messages, the remaining nodes are notified to delete the delivered messages and release the cache space in time after the messages are delivered to their destinations. The method suggested in this research can successfully lower the packet loss rate, minimize transmission latency and network overhead, and further increase the success rate of message delivery, according to experimental analysis and algorithm comparison.

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A Novel Opportunistic Network Routing Method on Campus Based on the Improved Markov Model

Despite its various benefits, the Mobile Ad-hoc Network (MANET) has a number of obstacles due to its mobility, unstable topology, energy efficiency, and other factors. In such an environment, routing protocols are required to transfer packets from source to destination. Due to the limited range of each mobile node's wireless broadcasts, some mobile nodes can operate as intermediary nodes to forward a packet to its destination. In MANET, the multipath routing technique is used to decrease the routing overhead. It can be accomplished by minimizing network traffic. This paper aims to reduce the routing overhead to improve the effectiveness of broadcasting messages successfully. The Position-based Opportunistic Routing protocol is used to identify the optimal routing path in the network. The opportunistic routing system is mostly employed in MANET data transmission to reduce overhead. This paper presented a hybrid routing algorithm with the combination of Emperor Penguin Optimization (EPO) and the Bald Eagle Search (BES) algorithm (EPO–BES) for finding the best-forwarded path to moderate the routing overhead problem in MANET. NS2 platform is utilized to perform the routing operation and compared with existing techniques such as NKR, PSO-GA, PSO-BLAP, QUACS, and SGC-MO. The proposed method has obtained higher PDR, path optimality, end-to-end delay, throughput, routing overhead, load balancing, and energy consumption than other approaches.

K. Bagirathan

Papers

Opportunistic Routing Protocol Based EPO–BES in MANET for Optimal Path Selection