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New technologies and the deployment of mobile and nomadic services are driving the emergence of complex communications networks, that have a highly dynamic behavior. This naturally engenders new route-discovery problems under changing conditions over these networks. Unfortunately, the temporal variations in the network topology are hard to be effectively captured in a classical graph model. In this paper, we use and extend a recently proposed graph theoretic model, which helps capture the evolving characteristic of such networks, in order to propose and formally analyze least cost journey (the analog of paths in usual graphs) in a class of dynamic networks, where the changes in the topology can be predicted in advance. Cost measures investigated here are hop count (shortest journeys), arrival date (foremost journeys), and time span (fastest journeys).

Wireless Sensor Networks (WSNs) are used for data collection from the surrounding environment using the enormous amount of sensor nodes. Energy saving is the most fundamental challenge of WSNs which primarily depends on the Cluster Head (CH) selection and packet routing strategy. In this paper, we are proposing an Energy Aware Distance-based Cluster Head selection and Routing (EADCR) protocol to extend the lifetime of WSN using the FCM technique, residual energy of the nodes, their relative Euclidean distances from the Base Station (BS) and cluster centroid. Since the nodes consume a considerable amount of energy during the clustering phase, thus to avoid this, here, we are introducing a new clustering approach where the CH selection is now based on the newly proposed fitness function. We are also providing a new strategy for packet routing using the shortest path technique for routing between node and its destination which reduces the energy consumption of the CHs by employing the multi-hop communication. We also save the energy of the nodes using their Euclidean distances among them, from their CH and from BS. The simulation results exhibit that the EADCR enhances the network lifetime as compared to the other similar algorithms, e.g., FCM, REHR, UCRA–GSO and CCA–GWO under different scenarios. It also saves the residual energy of the network and enhances the network coverage.

The applications of wireless sensor network (WSN) are growing very rapidly, so utilizing the energy in an efficient manner is a challenging task as the battery life of nodes in WSN is very limited. For enhancing the lifetime of the network, various clustering protocols have been proposed earlier. In this paper, a clustering protocol named Energy Efficient Clusterhead Selection Scheme (ECSS) is proposed. The proposed ECSS protocol focusses on selecting an energy-efficient cluster head (CH), which helps in enhancing the overall lifetime and performance of the network. The proposed ECSS protocol uses the energy levels of nodes for the CH selection process. The proposed protocol is designed for the heterogeneous environment and it aims in minimizing the energy usage in the network and thereby improving the lifespan of the network. To measure the performance of the proposed ECSS protocol, the comparison is performed with the various existing protocols using MATLAB simulator. The results of simulation show that the proposed ECSS protocol has enhanced the network lifespan, throughput, and energy usage of the network as contrasted to the existing protocols.

Circulant graphs have been extensively investigated over the past 30 years because of their broad application to different fields of theory and practice. Two known surveys on circulant networks including a survey on undirected circulants have been published: by Bermond et al. [Distributed loop computer networks: A survey, J. Parallel Distributed Comput.24 (1995) 2–10] and by Hwang [A survey on multi-loop networks, Theoret. Comput. Sci.299 (2003) 107–121]. The present paper includes the results which have not been presented there, in particular the works of Russian researchers, and also a lot of new results obtained in the area of research of circulant networks. We focus on the survey connected with study of structural and communicative properties of circulant networks.

In order to alleviate traffic congestion on multilayer networks, designing an efficient routing strategy is one of the most important ways. In this paper, a novel routing strategy is proposed to reduce traffic congestion on two-layer networks. In the proposed strategy, the optimal paths in the physical layer are chosen by comprehensively considering the roles of nodes’ degrees of the two layers. Both numerical and analytical results indicate that our routing strategy can reasonably redistribute the traffic load of the physical layer, and thus the traffic capacity of two-layer complex networks are significantly enhanced compared with the shortest path routing (SPR) and the global awareness routing (GAR) strategies. This study may shed some light on the optimization of networked traffic dynamics.

One of the major significant problems in the existing techniques in Wireless Sensor Networks (WSNs) is Energy Efficiency (EE) because sensor nodes are battery-powered devices. The energy-efficient data transmission and routing to the sink are critical challenges because WSNs have inherent resource limitations. On the other hand, the clustering process is a crucial strategy that can rapidly increase network lifetime. As a result, WSNs require an energy-efficient routing strategy with optimum route election. These issues are overcome by using Tasmanian Fully Recurrent Deep Learning Network with Pelican Variable Marine Predators Algorithm for Data Aggregation and Cluster-Based Routing in WSN (TFR-DLN-PMPOA-WSN) which is proposed to expand the network lifetime. Initially, Tasmanian Fully Recurrent Deep Learning Network (TFR-DLN) is proposed to elect the Optimal Cluster Head (OCH). After OCH selection, the three parameters, trust, connectivity, and QoS, are optimized for secure routing with the help of the Pelican Variable Marine Predators Optimization Algorithm (PMPOA). Finally, the proposed method finds the minimum distance among the nodes and selects the best routing to increase energy efficiency. The proposed approach will be activated in MATLAB. The efficacy of the TFR-DLN- PMPOA-WSN approach is assessed in terms of several performances. It achieves higher throughput, higher packet delivery ratio, higher detection rate, lower delay, lower energy utilization, and higher network lifespan than the existing methods.

Wireless Sensor Networks (WSNs) have come across several things which include collecting data, handling data and distribution for super visioning specific applications such as the services needed, managing anything that occurred naturally, etc. They totally rely on applications. Therefore, the WSNs are classified under major networks. This is very essential. It can be defined as a network of networks that helps in proper flow of data. The main characteristics of WSN include its continuous changes in topologies, connected nodes with several chips and tunic routing protocol. There should be the better utilization of the available resources so that its life span may exceed. There should be an effective usage of available assets to avoid the waste. In our research, we propose a hybrid approach, namely, the Power Control Tree-Based Cluster (PCTBC) to identify the Sybil attacks in WSNs. It employs several stages structured clustering of nodes based on position and identity verification. This approach is utilized for the usage of energy consumption, effectiveness of detecting Sybil attacks inside clusters. The main aspects put into consideration are the efficient routing protocol of the distance between the hops and the energy power remains, where the distance between the hops is being computed using the Received Signal Strength Indication (RSSI) and also the packet transmission can be properly tuned on the basis of the distance. Also, the proposed approach considers the energy consumption for the transmission of the defined packet.

Wireless Sensor Networks (WSN) became a novel technology for ubiquitous livelihood and still remains a hot research topic because of its applicability in diverse domains. Energy efficiency treated as a crucial factor lies in the designing of WSN. Clustering is commonly applied to increase the energy efficiency and reduce the energy utilization. The proper choice of cluster heads (CHs) and cluster sizes is important in a cluster-based WSN. The CHs which are placed closer to base station (BS) are affected by the hot spot issue and it exhausts its energy faster than the usual way. For addressing this issue, a new unequal clustering and routing technique using ant colony optimization (ACO) algorithm is presented. Initially, CHs are chosen and clusters are constructed based on several variables. Next, the ACO algorithm with levy distribution is applied for the selection of optimal paths between two nodes in the network. A comprehensive validation set takes place under diverse situations under the position of BS. The experimental outcome verified the superiority of the presented model under several validation parameters.

Opportunistic Mobile Social Networks (OMSNs), formed by mobile users with social relationships and characteristics, enhance spontaneous communication among users that opportunistically encounter each other. Such networks can be exploited to improve the performance of data forwarding. Discovering optimal relay nodes is one of the important issues for efficient data propagation in OMSNs. Although traditional centrality definitions to identify the nodes features in network, they cannot identify effectively the influential nodes for data dissemination in OMSNs. Existing protocols take advantage of spatial contact frequency and social characteristics to enhance transmission performance. However, existing protocols have not fully exploited the benefits of the relations and the effects between geographical information, social features and user interests. In this paper, we first evaluate these three characteristics of users and design a routing protocol called Geo-Social-Interest (GSI) protocol to select optimal relay nodes. We compare the performance of GSI using real INFOCOM06 data sets. The experiment results demonstrate that GSI overperforms the other protocols with highest data delivery ratio and low communication overhead.

Routing algorithm is an important factor and a key technology for Flying Ad hoc Networks (FANETs), which can safeguard FANET network communication. In FANETs, the fast-changing nature of FANET network topology makes the traditional Mobile Ad-hoc Networks (MANET) network routing algorithm not directly usable, which leads to challenges for the design of routing algorithms. In this paper, when the FANET nodes need to communicate, the route search program performs route search based on the ant colony algorithm, so as to obtain a stable route with high efficiency. Making use of NS3 for simulation of ACA, Dynamic Source Routing (DSR), and Ad hoc On demand Distance Vector Routing (AODV), the results of simulation show that ACA can improve FANET performance.

In this paper, a new algorithm is proposed for computing the node-disjoint optimal transmission energy consumption route for coded cooperative mobile IoT networks. Inspired by the potential benefits user cooperation can provide, we incorporate user cooperation to the mobile ad-hoc multi-hop IoT networks. Our results include a novel ant colony system-based node-disjoint energy-efficient routing algorithm. Ant colony system can approximate the optimal route by local information and is thus very suitable for mobile IoT network environment. In particular, ant algorithm makes history-sensitive choice and thus can significantly outperform the greedy algorithm. In addition, it can efficiently handle the case of multiple sources and multiple destinations. For a large IoT network, we investigate the multi-scale ant colony system and when compared to Dijkstra algorithm, such an algorithm usually shortens the runtime by a factor of several hundred.

In parallel and distributed systems, multistage interconnection network (MIN) plays an important role for its efficient communication between processor and memory at a very low cost. A major class of MIN called Gamma network is known for its redundant network topology and is being used in broadband communication systems. The increased redundancy incorporation makes these networks more complex and hence reliability evaluation becomes complex. The performance evaluation of these network topologies requires reliability evaluation utilizing routing mechanism or techniques. In this paper, we have proposed four topologies of Gamma-Minus network using MUX and DEMUX. Terminal Reliability (TR), fault tolerance and routing schemes of Gamma-Minus network topologies proposed have been computed by utilizing different connection patterns of MUX/DEMUX. Also, performance indices such as TR, Reliability Cost Ratio (RCR), Fault Tolerance, etc. computed for different Gamma-Minus architectures have been compared with the existing Gamma networks, other than Gamma-Minus. All the performance indices for different Gamma-Minus topologies show improvement over the performance indices of different Gamma networks. The proposed Gamma-Minus architectures have been compared among themselves and also Gamma-Minus2 shows the best performance for all performance indices. To the best of our knowledge, most of the researchers have not compared fault tolerance and RCR performance measure.

Since all the existing real world networks are evolving, the study of traffic dynamics is a challenging task. Avoidance of traffic congestion, system utility maximization and enhancement of network capacity are prominent issues. Network capacity may be improved either by optimizing network topology or enhancing in routing approach. In this context, we propose and design a model of the time-varying data communication networks (TVCN) based on the dynamics of inflowing links. Traffic congestion can be avoided by using a suitable centrality measure, especially betweenness and Eigen vector centralities. If the nodes coming in user’s route are most betweenness central, then that route will be highly congested. Eigen vector centrality is used to find the influence of a node on others. If a node is most influential, then it will be highly congested and considered as least reputed. For that reason, routes are chosen such that the sum of the centralities of the nodes coming in user’s route should be minimum. Furthermore, Kelly’s optimization formulation for a rate allocation problem is used for obtaining optimal rates of distinct users at different time instants and it is found that the user’s path with lowest betweenness centrality and highest reputation will always give maximum rate at the stable point.

The interconnetion network plays an important role in a parallel system. To avoid the edge number of the interconnect network scaling rapidly with the increase of dimension and achieve a good balance of hardware costs and properties, this paper presents a new interconnection network called exchanged $3$-ary $n$-cube ($E3C$). Compared with the $3$-ary $n$-cube structures, $E3C$ shows better performance in terms of many metrics such as small degree and fewer links. In this paper, we first introduce the structure of $E3C$ and present some properties of $E3C$; then, we propose a routing algorithm and obtain the diameter of $E3C$. Finally, we analyze the diagnosis of $E3C$ and give the diagnosibility under PMC model and MM* model.

We show that the edges of the modified Knödel graph can be grouped into dimensions which are similar to the dimensions of hypercubes. In particular, routing, broadcasting and gossiping, can be done easily in modified Knödel graphs using these dimensions.

The network properties of double and triple fixed step graphs are considered. We determine that the broadcast times of double and triple fixed step graphs of diameter D are equal to D+2 and D+3, respectively. Some results on the embeddings of grids into these graphs with dilation 1 and 2 are given. For a triple fixed step graph we give a method to calculate the routing between any two vertices of the graph. Furthermore, we show that the diameter of the surviving route graph remains two for any set F of faults for |F|=5, which is optimum.

Logistics delivery companies typically deal with delivery problems that are strictly constrained by time while ensuring optimality of the solution to remain competitive. Often, the companies depend on intuition and experience of the planners and couriers in their daily operations. Therefore, despite the variability-characterizing daily deliveries, the number of vehicles used every day are relatively constant. This motivates us towards reducing the operational variable costs by proposing an efficient heuristic that improves on the clustering and routing phases. In this paper, a decision support system (DSS) and the corresponding clustering and routing methodology are presented, incorporating the driver’s experience, the company’s historical data and Google map’s data. The proposed heuristic performs as well as $k$-means algorithm while having other notable advantages. The superiority of the proposed approach has been illustrated through numerical examples.

C-based cycle-accurate simulations are used to evaluate the performance of a Network-on-Chip (NoC) based on an improved version of the modified Fat Tree topology. The modification simplifies routing further and guarantee orderly reception of packets without any loss of performance. Several traffic models have been used in these simulations; Bursty and non-bursty traffic with uniformly-distributed destination addresses and non-uniformly-distributed destination addresses. A simple new traffic model has been developed for generating non-uniformly-distributed destination addresses. This model is general enough to be used in developing new NoC architectures and captures universally accepted place-and-route methodologies. Simulation results are used to illustrate how the hardware resources of a modified Fat Tree NoC can be minimized without affecting the network performance. The performance of a NoC with regular Mesh topology was also evaluated for comparison with the modified Fat Tree topology.

Gamma Interconnection Network (GIN) is characterized as Redundant Multistage Interconnection Network (MIN) which is considered as a potential candidate for use in broadband communications. Several advancements have been made to improve Reliability indices such as Terminal Reliability (TR), Broadcast Reliability (BR) and Network Reliability (NR) of these networks. But inspite of these advancements, there are certain issues which are yet to be explored such as Complexity, Cost, Number of disjoint paths on presumption that source/destination are failure free. Most of the work done in the literature addresses TR only and less work has been done on analysis of BR and NR. In literature networks, $8\times 8$ size has been explored and no attention has been paid to bigger network sizes although reliability of bigger size network is important for parallel processing systems. In this paper, existing class of Gamma Networks has been studied extensively and modifications have been proposed in existing Gamma Network which minimizes or resolves most of the limitations mentioned above. The proposed Gamma-Minus Network has more redundant paths than other networks. Proposed Network has been compared with some recently introduced members of this class. The results show that newly proposed Gamma-Minus Network has better reliability with lowest cost and path length and provides disjoint minimal-path set for $8\times 8$ to $1024\times 1024$ network size. The routing used in this paper eliminates the backtracking overhead which minimizes transmission delay.

The centralized planning and control that has defined the traditional information processing structure of manufacturing systems is no longer suited to the current rapidly changing manufacturing environment. For efficient use of manufacturing resources and increased flexibility, it is necessary to migrate to a distributed information processing system in which individual entities can work cooperatively towards overall system goals. The next generation of manufacturing systems requires such an information technology framework to integrate the system components and activities into a larger collaborative enterprise. This paper describes a multi-agent approach to concurrent design, manufacturability analysis, process planning, routing and scheduling. A heterogeneous multi-agent concurrent engineering system consisting of multiple feature-based design sub-systems, multiple simulated shop-floor resource groups, a supervisory control interface and the coordination mechanisms for multi-agent cooperation, has been developed. The architecture of this distributed system and the associated implementation issues are discussed.