Many-objective optimization (MaO) deals with a large number of conflicting objectives in optimization problems to acquire a reliable set of appropriate non-dominated solutions near the true Pareto front, and for the same, a unique mechanism is essential. Numerous papers have reported multi-objective evolutionary algorithms to explain the absence of convergence and diversity variety in many-objective optimization problems. One of the most encouraging methodologies utilizes many reference points to segregate the solutions and guide the search procedure. The above-said methodology is integrated into the basic version of the Moth Flame Optimization (MFO) algorithm for the first time in this paper. The proposed Many-Objective Moth Flame Optimization (MaOMFO) utilizes a set of reference points progressively decided by the hunt procedure of the moth flame. It permits the calculation to combine with the Pareto front yet synchronize the decent variety of the Pareto front. MaOMFO is employed to solve a wide range of unconstrained and constrained benchmark functions and compared with other competitive algorithms, such as non-dominated sorting genetic algorithm, multi-objective evolutionary algorithm based on dominance and decomposition, and novel multi-objective particle swarm optimization using different performance metrics. The results demonstrate the superiority of the algorithm as a new many-objective algorithm for complex many-objective optimization problems.

The present study examines the faculty staff’s socio-demographic factors (i.e., gender, academic ranking, and experience) as moderating variables on the relationship between the four interrelated factors (organizational, individual, technological, and client engagement) and their productivity (performance) during the Covid‐19 pandemic. A conceptual framework was developed by integrating several relevant studies in the field of Work from Home (WFH) productivity. To end this, we involved (n=388) academic staff working from home during the Covid-19 crisis to test the hypotheses in the higher education context. The findings showed that the academics’ WFH productivity was significantly associated with the four interrelated factors (organizational, individual, technological, and client-related factors) either collectively or individually, and the most important one was the individual-related factors. The moderation analysis reveals that the effect of the socio-demographic characteristics (gender, academic ranking, and experience) on WFH productivity was varied. Surprisingly, the study findings provided evidence for the first time that the client’s engagement (student) factor, which has not been studied before, was found as one of the main determinant factors of WFH productivity during the Covid-19 crisis.

The current mobile network core is built based on a centralized architecture, including the S-GW and P-GW entities to serve as mobility anchors. Nevertheless, this architecture causes non-optimal routing and latency for control messages. In contrast, the fifth generation (5G) network will redesign the network service architecture to improve changeover management and deliver clients a better Quality-of-Experience (QoE). To enhance the design of the existing network, a distributed 5G core architecture is introduced in this study. The control and data planes are distinct, and the core network also combines IP functionality anchored in a multi-session gateway design. We also suggest a control node that will fully implement the control plane and result in a flat network design. Its architecture, therefore, improves data delivery, mobility, and attachment speed. The performance of the proposed architecture is validated by improved NS3 simulation to run several simulations, including attachment and inter- and intra-handover. According to experimental data, the suggested network is superior in terms of initial attachment, network delay, and changeover management.

Ad hoc networks, known as infrastructure-less networks, are composed of mobile nodes that connect without a centralized system controlling them. These networks have a wide range of potential applications, including emergency response, events, military operations, wireless access, and intelligent transportation. They can take on various forms, such as wireless sensor networks, wireless mesh networks, and mobile ad hoc networks. Because users in these networks can move around at any time, routing protocols must adapt to the constantly changing network layout. However, these networks are also susceptible to various security threats, including DDoS attacks. This paper aims to analyze the performance and impact of security attacks on the performance of reactive and proactive routing protocols in CBR connection patterns with different pause times. The analysis is provided in metrics such as throughput, packet loss, end-to-end delay, and load. The simulation results show that, on average, the OPNET Modeler simulator analyzed the performance results under DDoS attacks under voice and video traffic conditions. Furthermore, the paper explores the use of Honeypot intelligent agents as a solution to increase security by creating a dummy node to fool DDoS attackers. The results show that the OLSR protocol is most affected by DDoS attacks in terms of quality-of-service metrics such as packet loss, throughput, end-to-end delay, and load. The number of responses to the honeypot solutions differs for each protocol.

This paper proposes a new variant of NTRU with a slightly different critical formulation. The significance of this new variant is that it requires an additional private key to provide a tighter scheme. Because of these changes, modified key generation, encryption and decryption algorithms have been developed accordingly. The new variant is analyzed and tested against several well-known attacks, namely the alternate private key attack, brute force attack, meet-in-the-middle attack, multiple transmission attacks and lattice attack. Security properties related to these attacks have been established and explored to ensure the new variant is secure against the said attacks. Several examples are provided to illustrate the ideas.