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Wireless sensor networks (WSNs) is associated with a new exemplification of a real-time embedded system used for various applications that make the traditional infrastructure-based network seem infeasible. Due to imbalanced energy consumption among nodes, WSN has challenges with better utilization of energy and system enhancement. Clustering has been a better approach in this sequence. Therefore, this paper will utilize a fuzzy logic-based clustering protocol (unequal clustering) with multi-hop transmission for load balancing, energy consumption minimization, and network lifetime prolongation. The protocol forms unequal clusters with cluster head (CH) being selected by fuzzy logic with competition radius. Node distance to the base station, concentration, and residual energy are input variables. The simulation and results section displays the outperformance of the proposed protocol, where the low-energy adaptive clustering hierarchy (LEACH), energy-aware multi-hop multi-path hierarchical (EAMMH), energy-aware unequal clustering fuzzy (EAUCF), and two-tier distributed fuzzy logic-based protocol (TTDFP) for efficient data aggregation in multi-hop wireless sensor networks algorithms.

Non-orthogonal multiple access (NOMA) and orthogonal frequency division multiple access (OFDMA) are two typical access techniques which can be applied for cellular systems. A hybrid scheme leveraging the advantages of NOMA and OMA schemes has been recently proved to be a promising approach to reduce the interference among users and enhance the performance of cellular device to device (D2D) networks. In this paper, we study the problem of resource allocation and mode selection for content fetching in a cellular D2D network. In order to improve the energy efficiency of the network, we formulate the joint problem as a system energy efficiency maximization problem. As this problem is a non-linear fractional problem that cannot be solved conveniently, we transform it into power allocation subproblem and content fetching mode selection subproblem, and then using the Lagrange dual method and a heuristic algorithm solve these two subproblems, respectively. The presented numerical results demonstrate the effectiveness of the proposed algorithm.

The network scalability and energy performance have great importance in wireless sensor networks (WSNs). WSN consists of a vast number of nodes with small memory and battery capacity, which makes an energy-efficient design of WSNs very essential. Since the entire network's life depends on the sensor nodes, effective energy usage, clustering has been proved one of the best approaches to enhance energy efficiency and network lifetime. In this paper, we design a type 2 fuzzy logic based clustering scheme in a multi-hop WSN to reduce energy consumption and improve network scalability. In this clustering scheme, we propose a Cluster head (CH) selection strategy where a sensor node is elected as a CH based on type 2 fuzzy logic inputs. To balance the load of CHs we also select their radius size based on the fuzzy logic inputs. We compare our proposed scheme with the well-known TTDPF and CHCCF schemes. The simulation results show that our proposed schemes outperform the TTDFP and CHCCF schemes in terms of network lifetime and other metrics.

The large issue looked by wireless sensor systems is security. Due to dynamic and synergistic nature of sensor organization, the associated sensor gadget makes the system unusable. The paper explains the utility of game theory in defensive wireless sensor networks (WSNs) from selfish nodes and malicious behavior. Game theory can effectively model WSNs malicious attacks because of its low complexity and scalability. The study, thus, explores different WSN defense strategies from both external attackers and internal nodes acting selfishly or maliciously using the game theory approach. Also, the paper highlights the general trust model for decision making using the game theory framework. Besides, the paper demonstrates the significance of the theory in ensuring WSN security from acute attacks and its role in enhancing trustworthiness in data and cooperation of nodes in various WSN architectures.

layer is key of wireless network. TDMA approach is based on Maximum utilization of frequency spectrum. Packet error is also depending on frequency spectrum. The demands of WLAN Devices day by day increases exponentially and it operates in the specific narrow spectrum of frequency bands and also increase communication parameters programmed and control over Most modern wireless devices. In this paper, simulate and analyze the performance of existing MAC layer protocol and hybrid MAC with TDMA protocol in wireless local Area Network is presented. In this simulation, we present a MAC protocol based on IEEE 802.11g standard in the DCF mode and DCF with TDMA mode which is useful to improve packet collision in traditional wireless networks. In this analysis, improved performance with TDMA base MAC layer is compared without TDMA. We used simulation through using NS-2 Simulator.

Enhancement the Performance of MANET (Mobile Ad-hoc Network) using spatial diversity. Spatial diversity implemented using cooperative transmission technique in Medium access control (MAC) layer level protocol. In noisy environment limit the network performance like coverage area, limit number of node, degrade packet transmission rate, increase packet loss rate etc. In this paper enhance the source to destination transmission range, minimize the packet loss, improve packet transmission rate and appropriate end to end delay. When direct link is fail to transmit packet then Cooperative scheme help to transmit packet. Cooperative scheme is to help the packet transmission with five handshakes instead of four. This scheme implemented in MANET network on MAC layer protocol. Cooperative scheme improve the performance with help of intermediate node between sources to destination. We are performance analysis using discrete simulator NS-2 in MANET. Our performance based on MAC layer level with cooperative scheme in IEEE WLAN standard CSMA/CA protocol.