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End-to-end latency in network affects the overall performance in number of ways. It is one of the major tasks to minimize the end-to-end latency in cognitive radio ad hoc networks (CRAHN), as the transmission of packets passes through every hop of the routing path. This paper aims to propose a new reactive multicast routing protocol, namely, improved frog leap inspired protocol (IFLIP) to reduce the overall end-to-end latency in CRAHN.

It is difficult to solve the problems that emerge in optimization. Routing is the procedure for choosing the best network path. This paper proposes a novel algorithm by improving the FLIP to use an ideal route, which progressively reduces the congestion level on various routing path by considering the spectrum accessibility and the service rate of each hop in CRAHN.

Result of this research work concludes that IFLIP significantly outperforms other baseline schemes (namely, TIGHT and Greedy TIGHT) in minimizing the end-to-end latency in CRAHN.

It is proved that IFLIP gives a better ratio of packet delivery under varying primary users and secondary users. IFLIP results in increased packet deliver ratio, reduced end-to-end latency and better throughput.

Cross-layer approach in media access control (MAC) layer will address interference and jamming problems. Hybrid distributed MAC can be used for simultaneous voice, data transmissions in wireless sensor network (WSN) and Internet of Things (IoT) applications. Choosing the correct objective function in Nash equilibrium for game theory will address fairness index and resource allocation to the nodes. Game theory optimization for distributed may increase the network performance. The purpose of this study is to survey the various operations that can be carried out using distributive and adaptive MAC protocol. Hill climbing distributed MAC does not need a central coordination system and location-based transmission with neighbor awareness reduces transmission power.

Distributed MAC in wireless networks is used to address the challenges like network lifetime, reduced energy consumption and for improving delay performance. In this paper, a survey is made on various cooperative communications in MAC protocols, optimization techniques used to improve MAC performance in various applications and mathematical approaches involved in game theory optimization for MAC protocol.

Spatial reuse of channel improved by 3%–29%, and multichannel improves throughput by 8% using distributed MAC protocol. Nash equilibrium is found to perform well, which focuses on energy utility in the network by individual players. Fuzzy logic improves channel selection by 17% and secondary users’ involvement by 8%. Cross-layer approach in MAC layer will address interference and jamming problems. Hybrid distributed MAC can be used for simultaneous voice, data transmissions in WSN and IoT applications. Cross-layer and cooperative communication give energy savings of 27% and reduces hop distance by 4.7%. Choosing the correct objective function in Nash equilibrium for game theory will address fairness index and resource allocation to the nodes.

Other optimization techniques can be applied for WSN to analyze the performance.

Game theory optimization for distributed may increase the network performance. Optimal cuckoo search improves throughput by 90% and reduces delay by 91%. Stochastic approaches detect 80% attacks even in 90% malicious nodes.

Channel allocations in centralized or static manner must be based on traffic demands whether dynamic traffic or fluctuated traffic. Usage of multimedia devices also increased which in turn increased the demand for high throughput. Cochannel interference keep on changing or mitigations occur which can be handled by proper resource allocations. Network survival is by efficient usage of valid patis in the network by avoiding transmission failures and time slots’ effective usage.

Literature survey is carried out to find the methods which give better performance.