Link Lifetime Research Articles

Energy- and trust-aware secure routing algorithm for big data classification using MapReduce framework in IoT networks

Due to the open nature of wireless data transmission, routing and data security pose an important research challenge in the Internet of Things (IoT)-enabled networks. Also, the characteristic features, like constrained resources, heterogeneity, uncontrolled environment, and scalability requirement, make the security issues even more challenging. Hence, an effective and secure routing protocol named modified Energy Harvesting Trust-aware Routing Algorithm (mod-EHTARA) is proposed to increase the energy efficiency and the lifespan of the nodes. The proposed mod-EHTARA is designed by adopting the Link Lifetime (LLT) model with the traditional EHTARA. The optimal secure routing path is effectively selected by the proposed mod-EHTARA using the cost metric, which considers the factors like delay, LLT, energy, and trust. The big data classification process is carried out at the Base Station (BS) using the MapReduce framework. Accordingly, the big data classification is progressed using a stacked autoencoder, which is trained by the Adaptive E-Bat algorithm. The Adaptive E-Bat algorithm is developed by integrating the adaptive concept with the Bat Algorithm (BA) and Exponential Weighted Moving Average (EWMA). The proposed mod-EHTARA showed better performance by obtaining a maximal energy of 0.9855.

A Stochastic Distribution Based Methodology to Estimate Control Phase Time for Software-Defined Radios in Tactical MANETs

Unlike commercial networks, the tactical networks drive in a critical environment and without a backbone infrastructure. These networks involve mission-critical operations that are dependent on the rapid and reliable transfer of delay-sensitive data to conduct command and control (C2). Owing to the decentralized and dynamic nature, tactical networks need to survive by maintaining seamless and simultaneous time-sensitive communication among software-defined radios (SDRs). Under mobility and dynamic network topology, link status continuously changes that cause substantial packet loss, and degrade network performance. It is challenging to maintain the connectivity between communicating nodes and find a suitable time for sending control messages (e.g., packet forwarding and route discovery), known as control phase time (CPT). Given a maximum transmission range for narrowband (NB) and wideband (WB) communication, the knowledge of link duration between communicating radios are of major concern, particularly for low latency and reliable communication requirements. Many existing techniques focus on topology control by exchanging mobility parameters in control transmissions, increasing the delay in data transmission. Therefore, it is a non-trivial task to calculate the expected time for the control transmissions due to the confrontation of speed and random movement of nodes. This paper presents a novel methodology to estimate a suitable time to execute the control phase based on the lifetime of communication links between SDRs in tactical MANETs. It uses stochastic distribution to make a network capable of effectively figuring out operative connectivity. The proposed methodology evaluates the maximum network connectivity based on the distances between communicating radios and radio transmission ranges for different quality-of-service (QoS) requirements. The simulation results validate that the proposed methodology’s CPT estimations are more appropriate for the timely link-formations in tactical radio MANETs. The proposed technique is generic and can be applied to any MANET environment using different mobility models.

Optimizing spectral efficiency based on poisson queuing model for procuring cognitive intelligence in vehicular communication

In vehicular networks, accidents and congestions constitute a significant risk due to numerous cause such as short link lifetime, spectrum competence and high mobility. Further, the shortage of spectrum is one of the significant concerns in vehicular communication. Hence, the competent supervision of spectrum utilization in vehicular networks is predominant. In vehicular communication, cognitive radio plays a crucial role to emphasize the implications of spectral proficiency. Henceforth, Poisson Queuing Model for procuring Cognitive Intelligence in Vehicular Communication (CIVC) is proposed to emphasize the purpose of spectrum in vehicular networks. The Poisson based queuing model deals with problems which involve waiting for specifics services (i.e., spectrum). Functional architecture is proposed to reduce both the bandwidth scarcity and spectrum inefficiency complication. Further, the proposed system aims to evaluate spectral competence for queuing model based on a single server and queuing model based on multiple servers. In addition to that, the proposed system model contemplates three main scenarios and (i.e.,) vehicle waiting time distribution, vehicle loss probability and vehicle time dissemination of server busy period, and the mathematical analysis evaluates the purpose of Cognitive Intelligence in vehicular communication using Deep learning.

Lifetime of links influences the evolution towards structural balance

A fully connected network is investigated with signed (friendly or hostile) links. We consider a time evolution which drives the network to a structurally balanced state. Usually a hypothesis is made tacitly that the states of links can be permanent. However in real networks these states can fluctuate. In this paper, we assign a lifetime to each link. When a link age exceeds its lifetime, its sign is substituted by a random value ±1 and its age is set to zero. Then, two asymptotic behaviors are observed. When the lifetime is large, the system is balanced with only small fluctuations. When the lifetime is short, the system fluctuates randomly, far from the balanced state. A crossover is observed between these two regimes. The age distribution of the links depends on the lifetime. The results are discussed in the context of data on selected conflicts between political actors in Europe and the Middle East in the XX century.

Tunicate swarm Grey Wolf optimization for multi-path routing protocol in IoT assisted WSN networks

Internet of Things (IoTs) have become popular for connected people as well as objects for collecting and exchanging data based on embedded sensors. In IoT-assisted Wireless sensor Networks (WSN), the nodes are considered as the resource parameters in several ways, like computing resources, energy resources, and storage resources such that the robust multipath routing protocols are needed for maintaining long network lifetime and for achieving higher energy utilization. Hence, this paper presents the multipath routing protocol using the proposed optimization method, named Tunicate swarm Grey Wolf optimization (TSGWO) algorithm in the IoT assisted WSN network. By multipath routing protocol, the multipath is designed by multipath source node to several destinations. The multipath source node forwarding packet to multiple destinations simultaneously. At first, the nodes in IoT-assisted WSN network is simulated together and performs the cluster head selection using Fractional Gravitational Search algorithm (FGSA), and then the multipath routing process is done on the basis of proposed TSGWO in which the routing path is selected by considering the fitness parameters, like QoS parameters and trust factors. The QoS parameters include the delay, energy, link lifetime, as well as distance. The path with the minimum distance is selected as optimal path using fitness parameter. The proposed optimization algorithm effectively performs the multipath routing mechanism by integrating the parametric features from both the optimization algorithm. After that, the route maintenance process is carried out in the simulated IoT network to recover the link breakage based on DRINA. The proposed TSGWO outperformed other methods with maximal average Residual energy of 2.161 J, maximal link lifetime of 0.075 s, maximal PDR of 96.38%, and maximal throughput of429.49 Kbps.

An efficient traffic contention and control mechanism to improve QoS in heterogeneous wireless sensor networks

<span>Heterogeneous Wireless Sensor Networks (HWSN) gathers information from a cooperative network. In HWSN, the sensor nodes are scattered and the major challenges are topology control, battery optimization, packet loss and link lifetime. The existing techniques do not concentrate on all the mentioned issues. The objective of this work is to provide congestion-free data transfer with higher throughput and increased packet delivery ratio. In the proposed methodology, three protocols are designed and developed, namely, Hop by Hop Rate Adjustment Protocol (HHRA), Energy Efficient Data Transfer Protocol (EEDT) and Alternative Routing Congestion Control Protocol (ARCC). The HHRA protocol senses the traffic in the channel and adjusts the transmission rate accordingly to avoid congestion. Secondly, the EEDT protocol is used to find specific nodes that are more efficient and transfer packets through those nodes to improve throughput. The ARCC protocol is used to redirect the path of transmission during the occurrence of congestion. Thus, the proposed traffic contention and control mechanisms ensures congestion free transmission and increases the packet delivery ratio by 23% and average throughput by 20% compared to the Dynamic Contention Window based Congestion Control (DCWCC) algorithm. </span>

Intersection Routing Based on Fuzzy Multi-Factor Decision for VANETs

Vehicular ad hoc network (VANET) is a special form of mobile ad hoc network (MANET), which plays a key role in the intelligent transportation system (ITS). Though many outstanding geographic routing protocols are designed for VANETs, a majority of them use parameters that only affect routing performance. In this article, we propose an intersection routing based on fuzzy multi-factor decision (IRFMFD), which utilizes several features. The scheme is divided into two parts, namely vehicular decision management and intersection decision management. In the vehicular component, candidate vehicles between two static nodes (SNs) located at two intersections derive potential routing paths considering distance, neighbor quantity, and relative velocity. In the intersection component, the candidate SN was chosen from the current intersection’s 2-hop neighbors which were connected with the current intersection by a route that was decided on in part one. To get the best scheme, we also introduced other factors to estimate the number of hops in each link and link lifetime. The simulation shows that the IRFMFD outperforms on delivery ratio and end-to-end delay compared with AODV (Ad hoc on-demand distance vector), GPSR (Greedy perimeter stateless routing) and GeOpps (Geographical opportunistic routing).

CS‐MAODV: Cuckoo search and M‐tree‐based multiconstraint optimal Multicast Ad hoc On‐demand Distance Vector Routing Protocol for MANETs

SummaryMobile ad hoc networks (MANETs) are a subclass of wireless ad hoc networks, having amazing qualities of dynamic network topology and moving nodes. As MANET changes its topology, routing is difficult at some moment. Routing protocol controls the stream of information and selects the efficient way to transmit the data. There are a variety of routing protocols existing in MANET. Accordingly, this paper presents the multicast routing protocol, named cuckoo search and M‐tree‐based multicast ad hoc on‐demand distance vector (CS‐MAODV) protocol for MANET. The proposed routing protocol includes a two‐step process, namely, M‐tree construction and optimal multicast route selection. Here, the divisional‐based cluster (DIVC) technique is used for building the M‐tree using three constraints: destination flag, path‐inclusion factor, and multifactor. Then, cuckoo search algorithm is used for selecting the optimal route by considering the multiple objectives, such as energy, link lifetime, distance, and delay. The performance of the proposed multicast routing protocol is analyzed, and the comparative analysis is performed with the existing routing protocols, such as MAODV, QoS‐based multicast routing protocol using reliable neighbor nodes selection (QMRPRNS), efficient fuzzy‐based multiconstraint protocol (EFMMRP), and energy‐efficient lifetime aware multicast route selection (EELAM). From the simulation results, it can be shown that the proposed CS‐MAODV protocol attains the maximum energy of 90.3513%, LLT of 158.7708 s, the throughput of 86.2226%, and PDR of 87.1606, respectively. Also, the proposed protocol has the minimum control overhead of 2.1415% and PDD of 0.0563 s.

Trust and Opportunity Based Routing Framework in Wireless Sensor Network Using Hybrid Optimization Algorithm

Opportunistic routing (OR) is the area of research in the trending scenario as the traditional methods for ensuring secure routing in the Wireless Sensor Networks (WSNs) suffer from the security and reliability issues. Though the existing multi-hop routing protocols are cheap and require less-intensive deployment, security is a major concern. The paper proposes the OR in WSNs using the hybrid optimization algorithm named, Monarch-Cat Swarm Optimization (M-CSO) which is the integration of Monarch Butterfly Optimization in Cat Swarm Optimization. The framework operates on two crucial aspects: one is to select the secure nodes and the other is to choose opportunistic nodes among selected secure nodes. The selection of secure nodes through the tolerant constant is based on the parameters of trust, connectivity, and QoS. The first two parameters are direct whereas, for QoS, Link Life Time and delay are considered to define it. Secondly, opportunistic nodes are optimally chosen through proposed M-CSO, based on the fitness parameters trust, distance, delay, and connectivity. The effectiveness of M-CSO based routing framework is evaluated using the performance metrics with 50 and 100 nodes in the presence of the attacks DoS, and Blackhole. The maximal detection rate, maximal throughput, minimum delay and minimum distance of the proposed M-CSO are 74.95, 77.7, 6.7 s and 102.67, respectively which is far better than competing methods Trust aware routing framework, Simple Opportunistic Adaptive Routing and Ant Colony Optimization for secured routing protocol. Moreover, M-CSO shows better performance as compared to the existing trust and opportunity based routing and optimization schemes.

Energy‐efficient multihop routing in WSN using the hybrid optimization algorithm

SummaryThe technical growth in the field of the wireless sensor networks (WSNs) has resulted in the process of collecting and forwarding the massive data between the nodes, which was a major challenge to the WSNs as it is associated with greater energy loss and delay. This resulted in the establishment of a routing protocol for the optimal selection of the multipath to progress the routing in WSNs. This paper proposes an energy‐efficient routing in WSNs using the hybrid optimization algorithm, cat–salp swarm algorithm (C‐SSA), which chooses the optimal hops in progressing the routing. Initially, the cluster heads (CHs) are selected using the low‐energy adaptive clustering hierarchy (LEACH) protocol that minimizes the traffic in the network. The CHs are engaged in the multihop routing, and the selection of the optimal paths is based on the proposed hybrid optimization, which chooses the optimal hops based on the energy constraints, such as energy, delay, intercluster distance, intracluster distance, link lifetime, delay, and distance. The simulation results prove that the proposed routing protocol acquired minimal delay of 0.3165 with 50 nodes and two hops, maximal energy of 0.1521 with 50 nodes and three hops, maximal number of the alive nodes as 39 with 100 nodes and two hops, and average throughput of 0.9379 with 100 nodes and three hops.

An Improved Heterogeneous Motion Prediction Algorithm for Vehicle-to-Vehicle Message Ferrying in VANETs

In infrastructure-less ad-hoc networks, the nodes can converse directly with other nodes without centralized servers. The vehicular networks are derived from the features of mobile ad-hoc networks (MANETs) whereas the message transmissions between the nodes are direct with each other or through some fixed terminals. But, a unique trademark is that the vehicle-to-vehicle ad-hoc links are poor because of extreme mobility which leads to frequent route breakage that causes emergency message delivery failure. The routing protocols availed in MANETS does not suit due to quick topology changes. The hop selection is based on the best cumulative communication duration that will be failing in some cases. Also, the worst/average case scenario is that the minimum connectivity to the source vehicle is not described in existing approaches. The core idea about the proposed research is to deliver data through an optimum path and to eliminate rupture link during the packet transmission. The system uses the Heterogeneous Motion Guess (HMG) algorithm for vehicular networks to set up a vested path. The HMG will select the relay vehicle's current position is near to the target vehicle plus the vehicle will opt the relay forwarder that has good radio coverage. The link lifetime of the selected hop should be greater than the minimum connectivity duration with the source vehicle. The selected vehicle will append the link expiry time and minimum connectivity duration in Route Demand Dispatch message in a unicast manner. This approach significantly minimizes the hop count numbers and improves the stability of the path. It radically predicts the link life, so the node can decide an alternative vested route. The simulation result shows how well the reactive demand-based HMG affords optimum results in terms of packet transmission success rate, average minimum hop counts, and communication delay.

Interference Management by Resource Exchange for D2D Communication in Cellular Network

Scarcity in communication spectrum in cellular network is one of the major challenges faced by the service providers around the world. Many efforts were put forth to manage the efficient spectrum distribution among various cells in the network. Reusing the resources by different cells in a safe distance without interference is the current mechanism to improve spectrum efficiency. Spectrum efficiency can be even improved by reusing the resources within a single cell. Device to Device (D2D) communication, a new technology boosts the spectrum reuse inside a cell in 5G. The major hurdle in implementing D2D is in the management of interference in a highly mobile environment. This high mobility risks the life-time of a D2D link and frequent shifting from D2D mode to normal cellular mode will occur. In this paper an effort is put forward to maintain the D2D link as long as possible through a resource exchange mechanism. The exchange occurs when interference by a cellular or D2D link threatens another D2D link. This approach can improve the life-time of a D2D link and thereby improving the consistency of the network.

Optimized Design and Challenges for C&L Band Optical Line Systems

Optical communications are the key enabler for the ever-increasing traffic growth as they allow multiplexing a number of carriers onto a single optical fiber. However, network deployments are becoming more challenging due to the large bandwidth increments. Indeed, the fiber planning process is a slow, costly, and strategic activity for network operators, who must decide where to rent or deploy additional capacity. Depending on the long-term view, the network operator will define a fiber plan which may require high capital expenditure (CAPEX) investments to deploy additional multiple fiber pairs between central offices. During the last few years, C&L-band technologies have evolved to a point where they are now strong candidates to extend the fiber lifetime of these high capacity links. This article aims to present the evolution of C&L-band systems from a network design perspective, covering transmission and optical amplifier capabilities, demand optimization phase, showing a record demonstration of 56.4 Tb/s C&L-band 800 km transmission using commercial C&L-band system technology.

A Multi-Path Routing Protocol Based on Link Lifetime and Energy Consumption Prediction for Mobile Edge Computing

During mobile edge computing, due to the movement of nodes and the exhaustion of node energy, link failure occurs thus reducing the network lifetime in the mobile ad-hoc network. When the route fails, because the single-path protocols need to restart the route discovery process, the delay of the network is greatly increased. Therefore, the multi-path routing protocol is proposed, saving the cost of route discovery. In this paper, we propose an ad hoc on-demand multi-path distance vector (AOMDV) routing protocol based on link lifetime and energy consumption prediction (named LLECP-AOMDV) for mobile edge computing. In the route discovery phase, the energy grading strategy is adopted. When the node energy is lower than the threshold, it no longer participates in the route discovery. In the routing selected phase, the path is selected based on the lifetime of the route link and the minimum energy consumption of the route. According to energy consumption, packet delivery rate, end-to-end delay performance indicators, we evaluate the comparison results. The result shows that under most network performance indicators and parameters, the proposed LLECP-AOMDV is superior to the other three protocols, which improves the network lifetime, reduces the node's energy consumption and the average end-to-end delay. The protocol is very useful for mobile edge computing.

Analysis of Route Stability in Mobile Multihop Networks Under Random Waypoint Mobility

Analytical performance evaluation is crucial in designing mobile multihop networks under different operational conditions. It provides the best insight into the effects of various network parameters and their interactions. The route and link lifetime in mobile multihop networks under a random mobility environment have significant effects on network performance. Many analytical studies have been introduced to the body of work concerned with the link and route lifetime in mobile multihop networks. However, there is no closed-form analytical study for link and route stability in MANETs under any random mobility model. In addition, to simplify the analysis, one or more network characteristics were not considered in most of related studies. This work presents a closed-form analytical model for the link and route lifetime in mobile multihop networks, where nodes move according to the random waypoint mobility model. The proposed model can capture the effects of most network characteristics including the number of mobile nodes, the number of hops, the network area size, the transmission range, and the speed of nodes. In addition, we used the proposed model to derive expressions for the bounds of the link and route lifetime under different network characteristics. The proposed model can help characterize the network performance, analyze the network as to meet a certain level of quality-of-service, and design better routing protocols to cope with link breakage caused by node mobility. To verify the proposed model, extensive simulations were performed under different network characteristics.

Link breakage maintenance and power-aware secure routing in MANET based on the Fuzzy Krill Herd-based Grasshopper optimization

As Mobile Ad hoc Networks (MANETs) are established using battery-powered nodes, the major concern to minimize the power consumption of the nodes is still a challenge while the lifetime of the network is taken into account. Thus, power-aware routing is the effective way to handle the situation that aims at minimizing the power consumption and network overhead in order to increase the network lifespan. Therefore, an effective power-aware secure routing protocol is designed using the proposed Fuzzy Krill Herd-based Grasshopper Optimization Algorithm (Fuzzy KH-GOA) such that the secure path is determined. Hence, it is evident that the routing path for transmitting the data packets is effectively decided using the proposed algorithm, which is based on the fitness parameters, such as fuzzy function, delay, distance, and power consumed by the path. The significance of this research relies on the link lifetime estimation for which the lifetime of the routes is detected in order to measure the link failure. The performance of the proposed Fuzzy KH-GOA reported the values of 23.858 J, 0.016 sec, 0.783, 0.840, and 10.908 sec, respectively in the absence of the attack and 22.624J, 22.624sec, 0.773, 0.812, and 9.862sec, respectively in the presence of attack for the measures, such as power, delay, Detection Rate (DR), throughput, and average Link Life Time.

Link Availability Based Routing Protocol for Mobile Ad-Hoc Networks based on Link Life Time Prediction

A self-configured MANET has a set of wireless devices. With no prior administration, the Mobile Nodes (MNs) communicate via the wireless links. The limited bandwidth, transmission errors, dynamic topology, energy constraints, and link stability fluctuations lead to node mobility. The links between nodes are unreliable and might break on account of such node mobility. Link breakage leads to the rerouting process at the sender node (where the link breakage occurs) or Source Node (SN). This work proposed Link availability based routing protocol (LBRP) for MANET to attain load balancing via the Multi-Path (MP) communication. The traffic data could completely pass through parallel multiple paths, which enhances the protocol efficiency. On weighing against the existing routing protocols (RPs), the LBRP chiefly considers frequent link failures and unpredictable change in topology. The simulation outcomes validate the proposed LBRP. The LBRP performs well when contrasted to the DSR, ZRP, and AODV in all the experiments. This work would serve as the groundwork for examining and optimizing certain network protocols, and could help in designing algorithms for transport control and medium access.

Aging-Resilient Topology Synthesis of Heterogeneous Manycore Network-On-Chip Using Genetic Algorithm with Flexible Number of Routers

As semiconductor processes enter the nanoscale, system-on-chip (SoC) interconnects suffer from link aging owing to negative bias temperature instability (NBTI), hot carrier injection (HCI), and electromigration. In network-on-chip (NoC) for heterogeneous manycore systems, there is a difference in the aging speed of links depending on the location and utilization of resources. In this paper, we propose a heterogeneous manycore NoC topology synthesis that predicts the aging effect of each link and deploys routers and error correction code (ECC) logic. Aging-aware ECC logic is added to each link to achieve the same link lifetime with less area and latency than the Bose-Chaudhuri-Hocquenghem (BCH) logic. Moreover, based on the modified genetic algorithm, we search for a solution that minimizes the average latency while ensuring the link lifetime by changing the number of routers, location, and network connectivity. Simulation results demonstrate that the aging-aware topology synthesis reduces the average latency of the network by up to 26.68% compared with the aging analysis and the addition of ECC logic on the link after the topology synthesis. Furthermore, topology synthesis with aging-aware ECC logic reduces the maximum average latency by up to 39.49% compared with added BCH logic.

Power optimization in MANET using topology management

Mobile ad-hoc network (MANET) is a wireless ad hoc network, which is quickly deployable and functions without any infrastructure. This work proposes a hybrid optimization algorithm, named Chronological-Earth Worm optimization Algorithm (C-EWA), for performing effective clustering and adjusts power and energy parameters using topology management. In this paper, initially a graph that is equivalent to the network is constructed, and then, clustering of the graph is performed using the proposed C-EWA to generate an optimal cluster head. C-EWA is developed by the integration of chronological theory in EWA, with the use of the objective function. Here, the objective function considers several factors that involve power, connectivity, mobility, link lifetime, and distance. After choosing appropriate clusters, each of the nodes that belong to the cluster constructs a Gabriel graph within the corresponding cluster. Once the Gabriel graph is constructed, each node updates the list of neighbor and maintains the graph connectivity and adjusts the power of transmission based on the connectivity. The performance of the proposed method shows superior performance in terms of remaining battery power, mobility, throughput, delay and connectivity with values of 21.960 J, 0.729, 0.713, 0.295, and 5.256, respectively.

Predicted Fitness Based Clustering Algorithm for Manets

Secure data delivery, mobility, link lifetime, energy consumption and delay are the most important parameters to be highly concentrated in the self-organised network named manets. Where in Manets the nodes move unpredictably in any direction with restricted battery life, resulting in frequent change in topology and due to mobility the trust in packet delivery will suffer inside the network. These constraints are studied broadly to ensure the secured data delivery and the lifetime of such networks. In this paper we propose a PFCA(Predicted fitness based clustering) algorithm using fitness value. The cluster heads are selected based on the fitness value of the nodes. Whereas the fitness value is calculated using the trust value, link lifetime for different type of node mobility and energy consumed and the clusters are formed using the PFCA clustering algorithm. The proposed PFC algorithm is experimented in the NS-2 network simulator and the results are compared with the existing PSO-clustering algorithm. The results show the effectiveness of our proposed algorithm in terms of network overhead, average number of clusters formed, average number of re-clustering required, delay and packet delivery ratio.