Showing papers on "Destination-Sequenced Distance Vector routing published in 2016"

ActiveTrust: Secure and Trustable Routing in Wireless Sensor Networks

Abstract: Wireless sensor networks (WSNs) are increasingly being deployed in security-critical applications Because of their inherent resource-constrained characteristics, they are prone to various security attacks, and a black hole attack is a type of attack that seriously affects data collection To conquer that challenge, an active detection-based security and trust routing scheme named ActiveTrust is proposed for WSNs The most important innovation of ActiveTrust is that it avoids black holes through the active creation of a number of detection routes to quickly detect and obtain nodal trust and thus improve the data route security More importantly, the generation and the distribution of detection routes are given in the ActiveTrust scheme, which can fully use the energy in non-hotspots to create as many detection routes as needed to achieve the desired security and energy efficiency Both comprehensive theoretical analysis and experimental results indicate that the performance of the ActiveTrust scheme is better than that of the previous studies ActiveTrust can significantly improve the data route success probability and ability against black hole attacks and can optimize network lifetime

Dynamic Routing for Flying Ad Hoc Networks

Abstract: This paper reports experimental results on self-organizing wireless networks carried by small flying robots. Flying ad hoc networks (FANETs) composed of small unmanned aerial vehicles (UAVs) are flexible, inexpensive, and fast to deploy. This makes them a very attractive technology for many civilian and military applications. Due to the high mobility of the nodes, maintaining a communication link between the UAVs is a challenging task. The topology of these networks is more dynamic than that of typical mobile ad hoc networks (MANETs) and of typical vehicle ad hoc networks. As a consequence, the existing routing protocols designed for MANETs partly fail in tracking network topology changes. In this paper, we compare two different routing algorithms for ad hoc networks: optimized link-state routing (OLSR) and predictive OLSR (P-OLSR). The latter is an OLSR extension that we designed for FANETs; it takes advantage of the Global Positioning System (GPS) information available on board. To the best of our knowledge, P-OLSR is currently the only FANET-specific routing technique that has an available Linux implementation. We present results obtained by both media-access-control (MAC) layer emulations and real-world experiments. In the experiments, we used a testbed composed of two autonomous fixed-wing UAVs and a node on the ground. Our experiments evaluate the link performance and the communication range, as well as the routing performance. Our emulation and experimental results show that P-OLSR significantly outperforms OLSR in routing in the presence of frequent network topology changes.

A survey on position-based routing for vehicular ad hoc networks

Abstract: Position-based routing is considered to be a very promising routing strategy for communication within vehicular ad hoc networks (VANETs), due to the fact that vehicular nodes can obtain position information from onboard global positioning system receivers and acquire global road layout information from an onboard digital map. Position-based routing protocols, which are based mostly on greedy forwarding, are well-suited to the highly dynamic and rapid-changing network topology of VANETs. In this paper, we outline the background and the latest development in VANETs and survey the state-of-the-art routing protocols previously used in VANETs. We present the pros and cons for each routing protocol, and make a detailed comparison. We also discuss open issues, challenges and future research directions. It is observed that a hybrid routing protocol is the best choice for VANETs in both urban and highway environments.

Spatial Reusability-Aware Routing in Multi-Hop Wireless Networks

Abstract: In the problem of routing in multi-hop wireless networks, to achieve high end-to-end throughput, it is crucial to find the “best” path from the source node to the destination node. Although a large number of routing protocols have been proposed to find the path with minimum total transmission count/time for delivering a single packet, such transmission count/time minimizing protocols cannot be guaranteed to achieve maximum end-to-end throughput. In this paper, we argue that by carefully considering spatial reusability of the wireless communication media, we can tremendously improve the end-to-end throughput in multi-hop wireless networks. To support our argument, we propose spatial reusability-aware single-path routing (SASR) and anypath routing (SAAR) protocols, and compare them with existing single-path routing and anypath routing protocols, respectively. Our evaluation results show that our protocols significantly improve the end-to-end throughput compared with existing protocols. Specifically, for single-path routing, the median throughput gain is up to 60 percent, and for each source-destination pair, the throughput gain is as high as $5.3\times$ ; for anypath routing, the maximum per-flow throughput gain is 71.6 percent, while the median gain is up to 13.2 percent.

Joint Clustering and Routing Design for Reliable and Efficient Data Collection in Large-Scale Wireless Sensor Networks

Abstract: For data collection in large-scale wireless sensor networks (WSNs), dynamic clustering provides a scalable and energy-efficient solution, which uses cluster head (CH) rotation and cluster range assignment algorithms to balance the energy consumption. Nevertheless, most existing works consider the clustering and routing as two isolated issues, which is harmful to the connectivity and energy efficiency of the network. In this paper, we provide a detailed analysis on the relations between clustering and routing, and then propose a joint clustering and routing (JCR) protocol for reliable and efficient data collection in large-scale WSN. JCR adopts the backoff timer and gradient routing to generate connected and efficient intercluster topology with the constraint of maximum transmission range. The relations between clustering and routing in JCR are further exploited by theoretical and numerical analyses. The results show that the multihop routing in JCR may lead to the unbalanced CH selection. Then, the solution is provided to optimize the network lifetime by considering the gradient of one-hop neighbor nodes in the setting of backoff timer. Theoretical analysis and simulation results prove the connectivity and efficiency of the network topology generated by JCR.

Ant colony optimization for the real-time train routing selection problem

Abstract: This paper deals with the real-time problem of scheduling and routing trains in a railway network. In the related literature, this problem is usually solved starting from a subset of routing alternatives and computing the near-optimal solution of the simplified routing problem. We study how to select the best subset of routing alternatives for each train among all possible alternatives. The real-time train routing selection problem is formulated as an integer linear programming formulation and solved via an algorithm inspired by the ant colonies’ behavior. The real-time railway traffic management problem takes as input the best subset of routing alternatives and is solved as a mixed-integer linear program. The proposed methodology is tested on two practical case studies of the French railway infrastructure: the Lille terminal station area and the Rouen line. The computational experiments are based on several practical disturbed scenarios. Our methodology allows the improvement of the state of the art in terms of the minimization of train consecutive delays. The improvement is around 22% for the Rouen instances and around 56% for the Lille instances.

An ant colony system empowered variable neighborhood search algorithm for the vehicle routing problem with simultaneous pickup and delivery

Abstract: The Vehicle Routing Problem with Simultaneous Pickup and Delivery is considered.A hybrid algorithm that combines ACS and VNS approach is developed.A number of well-known benchmark problems are solved and compared.Proposed algorithm outperformed perturbation based VNS and local search based ACS.Some new best solutions for benchmark problem instances are found. Along with the progress in computer hardware architecture and computational power, in order to overcome technological bottlenecks, software applications that make use of expert and intelligent systems must race against time where nanoseconds matter in the long-awaited future. This is possible with the integration of excellent solvers to software engineering methodologies that provide optimization-based decision support for planning. Since the logistics market is growing rapidly, the optimization of routing systems is of primary concern that motivates the use of vehicle routing problem (VRP) solvers as software components integrated as an optimization engine. A critical success factor of routing optimization is quality vs. response time performance. Less time-consuming and more efficient automated processes can be achieved by employing stronger solution algorithms. This study aims to solve the Vehicle Routing Problem with Simultaneous Pickup and Delivery (VRPSPD) which is a popular extension of the basic Vehicle Routing Problem arising in real world applications where pickup and delivery operations are simultaneously taken into account to satisfy the vehicle capacity constraint with the objective of total travelled distance minimization. Since the problem is known to be NP-hard, a hybrid metaheuristic algorithm based on an ant colony system (ACS) and a variable neighborhood search (VNS) is developed for its solution. VNS is a powerful optimization algorithm that provides intensive local search. However, it lacks a memory structure. This weakness can be minimized by utilizing long term memory structure of ACS and hence the overall performance of the algorithm can be boosted. In the proposed algorithm, instead of ants, VNS releases pheromones on the edges while ants provide a perturbation mechanism for the integrated algorithm using the pheromone information in order to explore search space further and jump from local optima. The performance of the proposed ACS empowered VNS algorithm is studied on well-known benchmarks test problems taken from the open literature of VRPSPD for comparison purposes. Numerical results confirm that the developed approach is robust and very efficient in terms of both solution quality and CPU time since better results provided in a shorter time on benchmark data sets is a good performance indicator.

An improved harmony search based energy-efficient routing algorithm for wireless sensor networks

Abstract: Graphical abstractDisplay Omitted HighlightsA new encoding of harmony memory for routing in WSNs has been proposed.A new generation method of a new harmony for routing in WSNs has been proposed.The dynamic adaptation is introduced for the parameter HMCR to improve the performance of the proposed routing algorithm.An effective local search strategy is proposed to improve the convergence speed and the accuracy of the proposed routing algorithm.An energy efficient objective function model is proposed. Wireless sensor networks (WSNs) is one of the most important technologies in this century. As sensor nodes have limited energy resources, designing energy-efficient routing algorithms for WSNs has become the research focus. And because WSNs routing for maximizing the network lifetime is a NP-hard problem, many researchers try to optimize it with meta-heuristics. However, due to the uncertain variable number and strong constraints of WSNs routing problem, most meta-heuristics are inappropriate in designing routing algorithms for WSNs. This paper proposes an Improved Harmony Search Based Energy Efficient Routing Algorithm (IHSBEER) for WSNs, which is based on harmony search (HS) algorithm (a meta-heuristic). To address the WSNs routing problem with HS algorithm, several key improvements have been put forward: First of all, the encoding of harmony memory has been improved based on the characteristics of routing in WSNs. Secondly, the improvisation of a new harmony has also been improved. We have introduced dynamic adaptation for the parameter HMCR to avoid the prematurity in early generations and strengthen its local search ability in late generations. Meanwhile, the adjustment process of HS algorithm has been discarded to make the proposed routing algorithm containing less parameters. Thirdly, an effective local search strategy is proposed to enhance the local search ability, so as to improve the convergence speed and the accuracy of routing algorithm. In addition, an objective function model that considers both the energy consumption and the length of path is developed. The detailed descriptions and performance test results of the proposed approach are included. The experimental results clearly show the advantages of the proposed routing algorithm for WSNs.

Energy Efficient Direction-Based PDORP Routing Protocol for WSN

Abstract: Energy consumption is one of the constraints in wireless sensor networks (WSNs). The routing protocols are the hot areas to address quality-of-service (QoS) related issues, viz., energy consumption, network lifetime, network scalability, and packet overhead. The key issue in WSN is that these networks suffer from the packet overhead, which is the root cause of more energy consumption and degrade the QoS in sensor networks. In WSN, there are several routing protocols, which are used to enhance the performance of the network. Out of those protocols, dynamic source routing (DSR) protocol is more suitable in terms of small energy density, but sometimes when the mode of a node changes from active to sleep, the efficiency decreases as the data packets need to wait at the initial point, where the packet has been sent and this increases the waiting time and end-to-end delay of the packets, which leads to increase in energy consumption. Our problem is to identify the dead nodes and to choose another suitable path so that the data transmission becomes smoother and less energy gets conserved. In order to resolve these issues, we propose directional transmission-based energy aware routing protocol named PDORP. The proposed protocol PDORP has the characteristics of both power efficient gathering sensor information system and DSR routing protocols. In addition, hybridization of genetic algorithm and bacterial foraging optimization is applied to proposed routing protocol to identify energy efficient optimal paths. The performance analysis, comparison through a hybridization approach of the proposed routing protocol, gives better result comprising less bit error rate, less delay, less energy consumption, and better throughput, which leads to better QoS and prolong the lifetime of the network. Moreover, the computation model is adopted to evaluate and compare the performance of the both routing protocols using soft computing techniques.

An Energy-Efficient Routing Algorithm for Software-Defined Wireless Sensor Networks

Abstract: Recent significant research on wireless sensor networks (WSNs) has led to the widespread adoption of software-defined WSNs (SDWSNs), which can be reconfigured even after deployment. In this paper, we propose an energy-efficient routing algorithm for SDWSNs. In this algorithm, to make the network to be functional, control nodes are selected to assign different tasks dynamically. The selection of control nodes is formulated as an NP-hard problem, taking into consideration of the residual energy of the nodes and the transmission distance. To tackle the NP-hard problem, an efficient particle swarm optimization algorithm is proposed. Simulation results show that the proposed algorithm performs well over other comparative algorithms under various scenarios.

A Branch-Price-and-Cut Algorithm for the Inventory-Routing Problem

Abstract: The inventory-routing problem IRP integrates two well-studied problems, namely, inventory management and vehicle routing. Given a set of customers to service over a multiperiod horizon, the IRP consists of determining when to visit each customer, which quantity to deliver in each visit, and how to combine the visits in each period into feasible routes such that the total routing and inventory costs are minimized. In this paper, we propose an innovative mathematical formulation for the IRP and develop a state-of-the-art branch-price-and-cut algorithm for solving it. This algorithm incorporates known and new families of valid inequalities, including an adaptation of the well-known capacity inequalities, as well as an ad hoc labeling algorithm for solving the column generation subproblems. Through extensive computational experiments on a widely used set of 640 benchmark instances involving between two and five vehicles, we show that our branch-price-and-cut algorithm clearly outperforms a state-of-the-art branch-and-cut algorithm on the instances with four and five vehicles. In this instance set, 238 were still open before this work and we proved optimality for 54 of them.

Secure and Robust Multi-Constrained QoS Aware Routing Algorithm for VANETs

Abstract: Secure QoS routing algorithms are a fundamental part of wireless networks that aim to provide services with QoS and security guarantees. In vehicular ad hoc networks (VANETs), vehicles perform routing functions, and at the same time act as end-systems thus routing control messages are transmitted unprotected over wireless channels. The QoS of the entire network could be degraded by an attack on the routing process, and manipulation of the routing control messages. In this paper, we propose a novel secure and reliable multi-constrained QoS aware routing algorithm for VANETs. We employ the ant colony optimisation (ACO) technique to compute feasible routes in VANETs subject to multiple QoS constraints determined by the data traffic type. Moreover, we extend the VANET-oriented evolving graph (VoEG) model to perform plausibility checks on the routing control messages exchanged among vehicles. Simulation results show that the QoS can be guaranteed while applying security mechanisms to ensure a reliable and robust routing service.

The multi-trip vehicle routing problem with time windows and release dates

Abstract: The multi-trip vehicle routing problem with time windows and release dates is a variant of the multi-trip vehicle routing problem where a time window and a release date are associated with each customer. The release date represents the date when the merchandise requested by a customer becomes available at the depot. The interest for this problem comes from the field of city logistics and the study of delivery systems involving City Distribution Centers (CDC). In these systems, goods are first delivered to a CDC before being transferred to eco-friendly vehicles for final delivery. We propose to address the problem through a population-based algorithm, with a giant tour representation for individuals. An efficient labeling procedure allows turning giant tours into solutions. Experiments demonstrate the effectiveness of the method.

An Energy-Efficient Region-Based RPL Routing Protocol for Low-Power and Lossy Networks

Abstract: Routing plays an important role in the overall architecture of the Internet of Things. IETF has standardized the RPL routing protocol to provide the interoperability for low-power and lossy networks (LLNs). LLNs cover a wide scope of applications, such as building automation, industrial control, healthcare, and so on. LLNs applications require reliable and energy-efficient routing support. Point-to-point (P2P) communication is a fundamental requirement of many LLNs applications. However, traditional routing protocols usually propagate throughout the whole network to discover a reliable P2P route, which requires large amount energy consumption. Again, it is challenging to achieve both reliability and energy-efficiency simultaneously, especially for LLNs. In this paper, we propose a novel energy-efficient region-based routing protocol (ER-RPL), which achieves energy-efficient data delivery without compromising reliability. In contrast of traditional routing protocols where all nodes are required for route discovery, the proposed scheme only requires a subset of nodes to do the job, which is the key of energy saving. Our theoretical analysis and extensive simulation studies demonstrate that ER-RPL has a great performance superiority over two conventional benchmark protocols, i.e., RPL and P2P-RPL.

Adaptive memetic algorithm for minimizing distance in the vehicle routing problem with time windows

Abstract: This paper presents an adaptive memetic algorithm to solve the vehicle routing problem with time windows (VRPTW). It is a well-known NP-hard discrete optimization problem with two objectives--to minimize the number of vehicles serving a set of geographically dispersed customers, and to minimize the total distance traveled in the routing plan. Although memetic algorithms have been proven to be extremely efficient in solving the VRPTW, their main drawback is an unclear tuning of their numerous parameters. Here, we introduce the adaptive memetic algorithm (AMA-VRPTW) for minimizing the total travel distance. In AMA-VRPTW, a population of solutions evolves with time. The parameters of the algorithm, including the selection scheme, population size and the number of child solutions generated for each pair of parents, are adjusted dynamically during the search. We propose a new adaptive selection scheme to balance the exploration and exploitation of the solution space. Extensive experimental study performed on the well-known Solomon's and Gehring and Homberger's benchmark sets confirms the efficacy and convergence capabilities of the proposed AMA-VRPTW. We show that it is very competitive compared with other state-of-the-art techniques. Finally, the influence of the proposed adaptive schemes on the AMA-VRPTW behavior and performance is investigated in a thorough sensitivity analysis. This analysis is complemented with the two-tailed Wilcoxon test for verifying the statistical significance of the results.

An ant colony optimization based routing algorithm for extending network lifetime in wireless sensor networks

Abstract: Reducing the energy consumption of network nodes is one of the most important problems for routing in wireless sensor networks because of the battery limitation in each sensor. This paper presents a new ant colony optimization based routing algorithm that uses special parameters in its competency function for reducing energy consumption of network nodes. In this new proposed algorithm called life time aware routing algorithm for wireless sensor networks (LTAWSN), a new pheromone update operator was designed to integrate energy consumption and hops into routing choice. Finally, with the results of the multiple simulations we were able to show that LTAWSN, in comparison with the previous ant colony based routing algorithm, energy aware ant colony routing algorithms for the routing of wireless sensor networks, ant colony optimization-based location-aware routing algorithm for wireless sensor networks and traditional ant colony algorithm, increase the efficiency of the system, obtains more balanced transmission among the nodes and reduce the energy consumption of the routing and extends the network lifetime.

Routing Optimization Under Uncertainty

Abstract: We consider a class of routing optimization problems under uncertainty in which all decisions are made before the uncertainty is realized. The objective is to obtain optimal routing solutions that ...

Secure Routing in Multihop Wireless Ad-Hoc Networks With Decode-and-Forward Relaying

Abstract: In this paper, we study the problem of secure routing in a multihop wireless ad-hoc network in the presence of randomly distributed eavesdroppers. Specifically, the locations of the eavesdroppers are modeled as a homogeneous Poisson point process (PPP) and the source-destination pair is assisted by intermediate relays using the decode-and-forward (DF) strategy. We analytically characterize the physical layer security performance of any chosen multihop path using the end-to-end secure connection probability (SCP) for both colluding and noncolluding eavesdroppers. To facilitate finding an efficient solution to secure routing, we derive accurate approximations of the SCP. Based on the SCP approximations, we study the secure routing problem, which is defined as finding the multihop path having the highest SCP. A revised Bellman–Ford algorithm is adopted to find the optimal path in a distributed manner. Simulation results demonstrate that the proposed secure routing scheme achieves nearly the same performance as exhaustive search.

An Efficient Tree-Based Self-Organizing Protocol for Internet of Things

Abstract: Tree networks are widely applied in sensor networks of Internet of Things (IoTs). This paper proposes an efficient tree-based self-organizing protocol (ETSP) for sensor networks of IoTs. In ETSP, all nodes are divided into two kinds: network nodes and non-network nodes. Network nodes can broadcast packets to their neighboring nodes. Non-network nodes collect the broadcasted packets and determine whether to join the network. During the self-organizing process, we use different metrics, such as number of child nodes, hop, communication distance, and residual energy to reach available sink nodes’ weight; the node with max weight will be selected as a sink node. Non-network nodes can be turned into network nodes when they join the network successfully. Then, a tree-based network can be obtained one layer by one layer. The topology is adjusted dynamically to balance energy consumption and prolong network lifetime. We conduct experiments with NS2 to evaluate ETSP. Simulation results show that our proposed protocol can construct a reliable tree-based network quickly. With the network scale increasing, the self-organization time, average hop, and packet loss ratio will not increase more. Furthermore, the success rate of packet in ETSP is much higher compared with $ad~hoc$ on demand distance vector routing and destination sequenced distance vector routing.

Performance comparison and detailed study of AODV, DSDV, DSR, TORA and OLSR routing protocols in ad hoc networks

Abstract: Communication among the wireless links between mobile nodes is become popular research area because of its simplicity of deployment and mobility. Collection of all mobile nodes through which all wireless links are connected called as Mobile Ad hoc Network (MANET). MANET network gets too much attraction of researchers due to its mobility, reliability, self-repairing, dynamic infrastructure and independent with the help of center administration. Despite of numerous advantages it has many problems like synchronization, routing protocol, delay and shortest path. Many routing protocols have been proposed like OLSR, DSDV, DSR, AODV and TORA so far to improve the routing performance therefore these routing protocols are studied in depth and simulated using NS-2. The simulation and comparison results will briefly present the impact of network size, packet delivery ratio, average delay and average throughput.

Consistent updates in software defined networks: On dependencies, loop freedom, and blackholes

Abstract: We consider the problem of finding efficient methods to update forwarding rules in Software Defined Networks (SDNs). While the original and updated set of rules might both be consistent, disseminating the rule updates is an inherently asynchronous process, resulting in potentially inconsistent states. We highlight the inherent trade-off between the strength of the consistency property and the dependencies it imposes among rule updates at different switches; these dependencies fundamentally limit how quickly the SDN can be updated. Additionally, we consider the impact of resource constraints and show that fast blackhole free migration of rules with memory limits is NP-hard for the controller. For the basic consistency property of loop freedom, we prove that maximizing the number of loop free update rules is NP-hard for interval-based routing and longest-prefix matching. We also consider the basic case of just one destination in the network and show that the greedy approach can be nearly arbitrarily bad. However, minimizing the number of not updated rules can be approximated well for destination-based routing. For applying all updates, we develop an update algorithm that has a provably minimal dependency structure. We also sketch a general architecture for consistent updates that separates the twin concerns of consistency and efficiency, and lastly, evaluate our algorithm on ISP topologies.

An adaptive large-neighborhood search heuristic for a multi-period vehicle routing problem

Abstract: This problem involves optimizing product collection and redistribution from production locations to a set of processing plants over a planning horizon. This horizon consists of several days, and the collection-redistribution is performed on a repeating daily basis. A single routing plan must be prepared for the whole horizon, taking into account the seasonal variations in the supply. We model the problem using a sequence of periods, each corresponding to a season. We propose an adaptive large-neighborhood search with several specifically designed operators and features. The results show the excellent performance of the algorithm in terms of solution quality and computational efficiency.

An improved formulation for the multi-depot open vehicle routing problem

Abstract: The multi-depot open vehicle routing problem (MDOVRP) is a recent hard combinatorial optimization problem that belongs to the vehicle routing problem family. In the MDOVRP, the vehicles depart from several depots and once they have delivered the goods to the last customers in their routes they are not required to return to the depots. In this work, we propose a new mixed integer programming formulation for the MDOVRP by improving some constraints from the literature and proposing new ones. The computational experience carried out over problem instances from the literature indicates that our proposed model outperforms the existing one.

A Predictive Cross-Layered Interference Management in a Multichannel MAC with Reactive Routing in VANET

Abstract: Vehicular ad hoc networks (VANETs) represent a particular mobile technology that permits communication between vehicles, offering security and comfort. Nowadays, distributed mobile wireless computing is becoming a very important communication paradigm, due to its flexibility to adapt to different mobile applications. In this work, an interference aware metric is proposed in order to reduce the level of interference between each pair of nodes at the MAC and routing layer. In particular, this metric with a prediction algorithm is proposed to work in a cross-layered MAC and an on-demand routing scheme in multi-radio vehicular networks, wherein each node is equipped with two multi-channel radio interfaces. The proposed metric is based on the maximization of the average signal-to-interference ratio (SIR) level of the connection between source and destination. In order to relieve the effects of the co-channel interference perceived by mobile nodes, transmission channels are switched on a basis of a periodical SIR evaluation. Our solution has been integrated with an on-demand routing scheme but it can be applied to other routing strategies. Three on-demand interference aware routing schemes integrating IEEE 802.11p Multi-channel MAC have been tested to assess the benefits of the novel metric applied to a vehicular context. NS-3 has been used for implementing and testing the proposed idea, and significant performance improvements were obtained: in particular, the proposed policy has resulted in an enhancement of network performance in terms of throughput and packet delivery ratio.

Energy-Efficient Routing Algorithm Based on Unequal Clustering and Connected Graph in Wireless Sensor Networks

Abstract: Clustering and multi-hop routing algorithms substantially prolong the lifetime of wireless sensor networks (WSNs). However, they also result in the energy hole and network partition problems. In order to balance the load between multiple cluster heads, save the energy consumption of the inter-cluster routing, in this paper, we propose an energy-efficient routing algorithm based on Unequal Clustering Theory and Connected Graph Theory for WSN. The new algorithm optimizes and innovates in two aspects: cluster head election and clusters routing. In cluster head election, we take into consideration the vote-based measure and the transmission power of sensor nodes when to sectionalize these nodes into different unequal clusters. Then we introduce the connected graph theory for inter-cluster data communication in clusters routing. Eventually, a connected graph is constituted by the based station and all cluster heads. Simulation results show that, this new algorithm balances the energy consumption among sensor nodes, relieves the influence of energy-hole problem, improve the link quality, achieves a substantial improvement on reliability and efficiency of data transmission, and significantly prolongs the network lifetime.

A Street-Centric Routing Protocol Based on Microtopology in Vehicular Ad Hoc Networks

Abstract: In a vehicular ad hoc network (VANET), high mobility and uneven distribution of vehicles are important factors affecting the performance of routing protocols. The high mobility may cause frequent changes of network topology, whereas the uneven distribution of vehicles may lead to routing failures due to network partition; even high density of vehicles may cause severe wireless channel contentions in an urban environment. In this paper, we propose a novel concept called the microtopology (MT), which consists of vehicles and wireless links among vehicles along a street as a basic component of routing paths and even the entire network topology. We abstract the MT model reflecting the dynamic routing-related characteristics in practical urban scenarios along streets, including the effect of mobility of vehicles, signal fading, wireless channel contention, and existing data traffic. We first analyze the endside-to-endside routing performance in an MT as a basis of routing decision. Then, we propose a novel street-centric routing protocol based on MT (SRPMT) along the streets for VANETs. Simulation results show that our proposed SRPMT protocol achieves higher data delivery rate and shorter average end-to-end delay compared with the performance of greedy perimeter stateless routing (GPSR) and greedy traffic-aware routing (GyTAR).