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Multimedia applications such as digital audio and video have stringent quality of service (QoS) requirement in mobile ad hoc network. To support wide range of QoS, complex routing protocols with multiple QoS constraints are necessary. In QoS routing, the basic problem is to find a path that satisfies multiple QoS constraints. Moreover, mobility, congestion and packet loss in dynamic topology of network also leads to QoS performance degradation of protocol.

In this paper, the authors proposed a multi-path selection scheme for QoS aware routing in mobile ad hoc network based on fractional cuckoo search algorithm (FCS-MQARP). Here, multiple QoS constraints energy, link life time, distance and delay are considered for path selection.

The experimentation of proposed FCS-MQARP is performed over existing QoS aware routing protocols AOMDV, MMQARP, CS-MQARP using measures such as normalized delay, energy and throughput. The extensive simulation study of the proposed FCS-based multipath selection shows that the proposed QoS aware routing protocol performs better than the existing routing protocol with maximal energy of 99.1501 and minimal delay of 0.0554.

This paper presents a hybrid optimization algorithm called the FCS algorithm for the multi-path selection. Also, a new fitness function is developed by considering the QoS constraints such as energy, link life time, distance and delay.

Resilient route selection for oversized cargoes, one of the general bulk cargoes, has not been adequately optimized in terms of using the Arctic route. This study solves the problem of selecting the optimal shipping routes for oversized cargoes from Busan (South Korea) to Balkhash (Kazakhstan).

The study used the consistent fuzzy preference relation (CFPR) method, which is used to solve multi-criteria decision-making (MCDM) and uncertainty problems, to tackle the route selection. This method involves three procedures: first, the critical factors and alternative routes were obtained by the previous literature and an in-depth interview of experts of oversized cargo-handling with more than 20 years of working experience; second, the weightings for each critical factor were identified using the CFPR calculation process and third, alternative routes were evaluated using weighted critical factors.

The Northern Sea Route (NSR) combined with the inland waterways of Russia and Kazakhstan was first suggested for bulk carriers that handle oversized cargoes. The NSR could be a suitable route from Busan to Cape Kamenny of the Russian transshipment seaport, where oversized cargoes will be transferred to the river barge at Cape Kamenny, covering 4,913 km from the latter to Balkhash of Kazakhstan via the Ob/Irtysh River.

This study equips stakeholders in route selection for cargoes with strategies and methods to improve transportation efficiently and enhance shipping routes between Asia and the Commonwealth of Independent States (CIS). In addition to oversized cargoes, coal and timber from Russia can be transported to Asia using inland waterways and the NSR, which can also be used to transport plant equipment for petroleum refineries among Asian countries.

This is the first study to evaluate the suitability of the Artic route for oversized cargoes from South Korea to Kazakhstan. It provides a comprehensive evaluation framework of multimodal shipping routes and offers references for decision-makers when dealing with similar problems.

Routing protocol for low-power lossy network (RPL) being the de facto routing protocol used by low power lossy networks needs to provide adequate routing service to mobile nodes (MNs) in the network. As RPL is designed to work under constraint power requirements, its route updating frequency is not sufficient for MNs in the network. The purpose of this study is to ensure that MNs enjoy seamless connection throughout the network with minimal handover delay.

This study proposes a load balancing mobility aware secure hybrid – RPL in which static node (SN) identifies route using metrics like expected transmission count, and path delay and parent selection are further refined by working on remaining energy for identifying the primary route and queue availability for secondary route maintenance. MNs identify route with the help of smart timers and by using received signal strength indicator sampling of parent and neighbor nodes. In this work, MNs are also secured against rank attack in RPL.

This model produces favorable result in terms of packet delivery ratio, delay, energy consumption and number of living nodes in the network when compared with different RPL protocols with mobility support. The proposed model reduces packet retransmission in the network by a large margin by providing load balancing to SNs and seamless connection to MNs.

In this work, a novel algorithm was developed to provide seamless handover for MNs in network. Suitable technique was developed to provide load balancing to SNs in network by maintaining appropriate secondary route.

This study aims to propose a framework for designing appropriate triangular fuzzy numbers in a fuzzy analytic hierarchy process (FAHP) for selecting a road freight transport route and investigate the appropriate fuzzy numbers determined from a reliable consensus among participating experts based on the Delphi method.

The fundamental nine-point scale was investigated and separated into nonfuzzy intervals for importance assessment. A total of 17 individual experts participated in this study, and their consensus was that appropriate fuzzy numbers could be obtained using a three-round Delphi process. Moreover, the appropriate fuzzy numbers were used instead of the primary fuzzy numbers to calculate the relative weights of the decision criteria for road freight route selection.

The results confirmed that the Delphi method can be easily and rigorously applied to define appropriate fuzzy numbers. Further, this framework can serve as a guideline for a situation wherein the input of other fuzzy multiple criteria decision-making tools must be provided.

The FAHP has been widely used to address the imprecise assessments of decision-makers. However, most existing studies on the incorporation of such techniques have not defined fuzzy numbers, which are relevant to the problem of interest. This study contributes by incorporating the Delphi method that can design an appropriate fuzzy number for road freight route selection.

Wireless sensor networks (WSN) have been widely adopted for various applications due to their properties of pervasive computing. It is necessary to prolong the WSN lifetime; it avails its benefit for a long time. WSN lifetime may vary according to the applications, and in most cases, it is considered as the time to the death of the first node in the module. Clustering has been one of the successful strategies for increasing the effectiveness of the network, as it selects the appropriate cluster head (CH) for communication. However, most clustering protocols are based on probabilistic schemes, which may create two CH for a single cluster group, leading to cause more energy consumption. Hence, it is necessary to build up a clustering strategy with the improved properties for the CH selection. The purpose of this paper is to provide better convergence for large simulation space and to use it for optimizing the communication path of WSN.

This paper plans to develop a new clustering protocol in WSN using fuzzy clustering and an improved meta-heuristic algorithm. The fuzzy clustering approach is adopted for performing the clustering of nodes with respective fuzzy centroid by using the input constraints such as signal-to-interference-plus-noise ratio (SINR), load and residual energy, between the CHs and nodes. After the cluster formation, the combined utility function is used to refine the CH selection. The CH is determined based on computing the combined utility function, in which the node attaining the maximum combined utility function is selected as the CH. After the clustering and CH formation, the optimal communication between the CH and the nodes is induced by a new meta-heuristic algorithm called Fitness updated Crow Search Algorithm (FU-CSA). This optimal communication is accomplished by concerning a multi-objective function with constraints with residual energy and the distance between the nodes. Finally, the simulation results show that the proposed technique enhances the network lifetime and energy efficiency when compared to the state-of-the-art techniques.

The proposed Fuzzy+FU-CSA algorithm has achieved low-cost function values of 48% to Fuzzy+Particle Swarm Optimization (PSO), 60% to Fuzzy+Grey Wolf Optimizer (GWO), 40% to Fuzzy+Whale Optimization Algorithm (WOA) and 25% to Fuzzy+CSA, respectively. Thus, the results prove that the proposed Fuzzy+FU-CSA has the optimal performance than the other algorithms, and thus provides a high network lifetime and energy.

For the efficient clustering and the CH selection, a combined utility function was developed by using the network parameters such as energy, load, SINR and distance. The fuzzy clustering uses the constraint inputs such as residual energy, load and SINR for clustering the nodes of WSN. This work had developed an FU-CSA algorithm for the selection of the optimal communication path for the WSN.

The purpose of this paper is to provide a traffic route selection strategy based on minimum carbon dioxide (CO₂) emission by vehicles over different route choices.

The study used queuing theory for Markovian M/M/1 model over the road junctions to assess total time spent over each of the junctions for a route with junctions in tandem. With parameters of distance, mean service rate at the junction, the number of junctions and fuel consumption rate, which is a function of variable average speed, the CO₂ emission is estimated over each of the junction in tandem and collectively over each of the routes.

The outcome of the study is a mathematical formulation, using queuing theory to estimate CO₂ emissions over different route choices. Research finding estimated total time spent and subsequent CO₂ emission for mean arrival rates of vehicles at junctions in tandem. The model is validated with a pilot study, and the result shows the best vehicular route choice with minimum CO₂ emissions.

Proposed study is limited to M/M/1 model at each of the junction, with no defection of vehicles. The study is also limited to a constant mean arrival rate at each of the junction.

The work can be used to define strategies to route vehicles on different route choices to reduce minimum vehicular CO₂ emissions.

Proposed work gives a solution for minimising carbon emission over routes with unsignalised junctions in the tandem network.

The purpose of this paper is to investigate the latest research related to secure routing protocols in Wireless Sensor Network (WSN) and propose a new approach that can achieve a higher security level compared to the existing one. One of the main security issues in WSNs is the security of routing protocols. A typical WSN consists of a large number of small size, low-power, low-cost sensor devices. These devices are very resource-constrained and usually use cheap short-range radios to communicate with each other in an ad hoc fashion thus, achieving security in these networks is a big challenge, which is open for research.

The route updates and data messages of the protocol are authenticated using Edwards-curves Digital Signature Algorithm (EdDSA). Routing protocols play an essential role in WSNs, they ensure the delivery of the sensed data from the remote sensor nodes to back-end systems via a data sink. Routing protocols depend on route updates received from neighboring nodes to determine the best path to the sink. Manipulating these updates by inserting rouge nodes in the network that advertise false updates can lead to a catastrophic impact on the compromised WSN performance.

As a result, a new secure energy-aware routing protocol (SEARP) is proposed, which uses security enhanced clustering algorithm and EdDSA to authenticate route advertisements and messages. A secure clustering algorithm is also used as part of the proposed protocol to conserve energy, prolong network lifetime and counteract wormhole attacks.

In this paper, a SEARP is proposed to address network layer security attacks in WSNs. A secure clustering algorithm is also used as part of the proposed protocol to conserve energy, prolong network lifetime and counteract wormhole attacks. A simulation has been carried out using Sensoria Simulator and the performance evaluation has been discussed.

The purpose of this paper is to take advantage of Internet of Things (IoT) for intelligent route programming of crowd emergency evacuation in metro station. It is a novel approach to ensure the crowd safety and reduce the casualties in the emergency context. An evacuation route programming model is constructed to select a suitable evacuation route and support the emergency decision maker of metro station.

The IoT technology is employed to collect and screen information, and to construct an expert decision model to support the metro station manager to make decision. As a feasible way to solve the multiple criteria decision-making problem, an improved multi-attributive border approximation area comparison (MABAC) approach is introduced.

The case study indicates that the model provides valuable suggestions for evacuation route programming and offers practical support for the design of an evacuation route guidance system. Moreover, IoT plays an important role in the process of intelligent route programming of crowd emergency evacuation in metro station. A library has similar structure and crowd characteristics of a metro station, thus the intelligent route programming approach can be applied to the library crowd evacuation.

The highlights of this paper are listed as followings: the accuracy and accessibility of the metro station’s real-time information are improved by integrating IoT technology with the intelligent route programming of crowd emergency evacuation. An improved MABAC approach is introduced to the expert support model. It promotes the applicability and reliability of decision making for emergency evacuation route selection in metro station. It is a novel way to combine the decision-making methods with practice.

Security is the major issue that motivates multiple scholars to discover security solutions apart from the advantages of wireless sensor networks (WSN) such as strong compatibility, flexible communication and low cost. However, there exist a few challenges, such as the complexity of choosing the expected cluster, communication overhead, routing selection and the energy level that affects the entire communication. The ultimate aim of the research is to secure data communication in WSN using prairie indica optimization.

Initially, the network simulator sets up clusters of sensor nodes. The simulator then selects the Cluster Head and optimizes routing using an advanced Prairie Indica Optimization algorithm to find the most efficient communication paths. Sensor nodes collect data, which is securely transmitted to the base station. By applying prairie indica optimization to WSNs, optimize key aspects of data communication, including secure routing and encryption, to protect sensitive information from potential threats.

The Prairie Indica Optimization, as proposed, achieves impressive results for networks comprising 50 nodes, with delay, energy and throughput values of 77.39 ms, 21.68 J and 22.59 bps. In the case of 100-node networks, the achieved values are 80.95 ms, 27.74 J and 22.03 bps, significantly surpassing the performance of current techniques. These outcomes underscore the substantial improvements brought about by the Prairie Indica Optimization in enhancing WSN data communication.

In this research, the Prairie Indica Optimization is designed to enhance the security of data communication within WSN.

With the rapid growth of wireless sensor networks (WSNs), they have become an integral and substantial part of people's life. As such WSN stands as an assuring outlook, but because of sensor's resource limitations and other prerequisites, optimal dual route discovery becomes an issue of concern. WSN along with central sink node is capable of handling wireless transmission, thus optimizing the network's lifetime by selecting the dual path. The major problem confronted in the application of security mechanisms in WSNs is resolving the issues amid reducing consumption of resources and increases security.

According to the proposed system, two metrics, namely, path length and packets delivery ratio are incorporated for identifying dual routes amid the source and destination. Thereafter by making use of the distance metric, the optimal dual route is chosen and data transmission is carried out amid the nodes. With the usage of the recommended routing protocol high packet delivery ratio is achieved with reduced routing overhead and low average end to end delay. It is clearly portrayed in the simulation output that the proposed on demand dual path routing protocol surpasses the prevailing routing protocol. Moreover, security is achieved make use of in accord the data compression reduces the size of the data. With the help of dual path, mathematical model of Finite Automata Theory is derived to transmit data from source to destination. Finite Automata Theory comprises Deterministic Finite Automata (DFA) that is being utilized for Dual Path Selection. In addition, data transition functions are defined for each input stage. In this proposed work, another mathematical model is 10; introduced to efficiently choose an alternate path between a receiver and transmitter for data transfer with qualified node as relay node using RR Algorithm. It also includes Dynamic Mathematical Model for Node Localization to improve the precision in location estimation using Node Localization Algorithm. As a result a simulator is built and various scenarios are elaborated for comparing the performance of the recommended dual path routing protocol with respect to the prevailing ones.

Reliability and fault-tolerance: The actual motive in utilizing the approach of multipath routing in sensor network was to offer path resilience in case of a node or link failures thus ascertaining reliable transmission of data. Usually in a fault tolerant domain, when the sensor node is unable to forward the data packets to the sink, alternative paths can be utilized for recovering its data packets during the failure of any link/node. Load balancing: Load balancing involves equalizing energy consumption of all the existing nodes, thereby degrading them together. Load balancing via clustering improves network scalability. The network's lifetime as well as reliability can be extended if varied energy level's nodes exist in sensor node. Quality of service (QoS): Improvement backing of quality of service with respect to the data delivery ratio, network throughput and end-to-end latency stands very significant in building multipath routing protocols for various network types. Reduced delay: There is a reduced delay in multipath routing since the backup routes are determined at the time of route discovery. Bandwidth aggregation: By dividing the data toward the same destination into multiple streams (by routing all to a separate path) can aggregate the effective bandwidth. The benefit being that, in case a node possesses many links with low bandwidth, it can acquire a bandwidth which is more compared to the individual link.

Few more new algorithms can be used to compare the QoS parameters.

Proposed mechanism with feedback ascertains improvised delivery ratio compared to the single path protocol since in case of link failure, the protocol has alternative route. In case there are 50 nodes in the network, the detection mechanism yields packet delivery of 95% and in case there are 100 nodes, the packet delivery is lowered to 89%. It is observed that the packet rate in the network is more for small node range. When the node count is 200, the packet ratio is low, which is lowered to 85%. With a node count of 400, the curve depicts the value of 87%. Hence, even with a decrease in value, it is superior than the existing protocols. The average end-to-end delay represents the transmission delay of the data packets that have been successfully delivered as depicted in Figure 6 and Table 3. The recommended system presents the queue as well as the propagation delay from the source to destination. The figure depicts that when compared to the single path protocol, the end-to-end delay can be reduced via route switching. End-to-end delay signifies the time acquired for the delay in the receival of the the retransmitted packet by each node. The comparison reveals that the delay was lower compared to the existing ones in the WSN. Proposed protocol aids in reducing consumption of energy in transmitter, receiver and various sensors. Comparative analysis of energy consumptions of the sensor in regard to the recommended system must exhibit reduced energy than the prevailing systems.

On demand dual path routing protocol. Hence it is verified that the on demand routing protocol comprises DFA algorithms determines dual path. Here mathematical model for routing between two nodes with relay node is derived using RR algorithm to determine alternate path and thus reduce energy consumption. Another dynamic mathematical model for node localization is derived using localization algorithm. For transmitting data with a secure and promising QoS in the WSNs, the routing optimization technique has been introduced. The simulation software environment follows the DFA. The simulation yields in improvised performance with respect to packet delivery ratio, throughput, average end-to-end delay and routing overhead. So, it is proved that the DFA possesses the capability of optimizing the routing algorithms which facilitates the multimedia applications over WSNs.