Showing papers on "Hazy Sighted Link State Routing Protocol published in 2018"
TL;DR: This article proposes a new, real-time deep learning based intelligent network traffic control method, exploiting deep Convolutional Neural Networks (deep CNNs) with uniquely characterized inputs and outputs to represent the considered Wireless Mesh Network (WMN) backbone.
Abstract: Recently, deep learning has appeared as a breakthrough machine learning technique for various areas in computer science as well as other disciplines. However, the application of deep learning for network traffic control in wireless/heterogeneous networks is a relatively new area. With the evolution of wireless networks, efficient network traffic control such as routing methodology in the wireless backbone network appears as a key challenge. This is because the conventional routing protocols do not learn from their previous experiences regarding network abnormalities such as congestion and so forth. Therefore, an intelligent network traffic control method is essential to avoid this problem. In this article, we address this issue and propose a new, real-time deep learning based intelligent network traffic control method, exploiting deep Convolutional Neural Networks (deep CNNs) with uniquely characterized inputs and outputs to represent the considered Wireless Mesh Network (WMN) backbone. Simulation results demonstrate that our proposal achieves significantly lower average delay and packet loss rate compared to those observed with the existing routing methods. We particularly focus on our proposed method's independence from existing routing protocols, which makes it a potential candidate to remove routing protocol(s) from future wired/ wireless networks.
221 citations
TL;DR: Simulation results demonstrate that EDGR exhibits higher energy efficiency, and has moderate performance improvements on network lifetime, packet delivery ratio, and delivery delay, compared to other geographic routing protocols in WSNs over a variety of communication scenarios passing through routing holes.
Abstract: Geographic routing has been considered as an attractive approach for resource-constrained wireless sensor networks (WSNs) since it exploits local location information instead of global topology information to route data. However, this routing approach often suffers from the routing hole (i.e., an area free of nodes in the direction closer to destination) in various environments such as buildings and obstacles during data delivery, resulting in route failure. Currently, existing geographic routing protocols tend to walk along only one side of the routing holes to recover the route, thus achieving suboptimal network performance such as longer delivery delay and lower delivery ratio. Furthermore, these protocols cannot guarantee that all packets are delivered in an energy-efficient manner once encountering routing holes. In this paper, we focus on addressing these issues and propose an energy-aware dual-path geographic routing (EDGR) protocol for better route recovery from routing holes. EDGR adaptively utilizes the location information, residual energy, and the characteristics of energy consumption to make routing decisions, and dynamically exploits two node-disjoint anchor lists, passing through two sides of the routing holes, to shift routing path for load balance. Moreover, we extend EDGR into three-dimensional (3D) sensor networks to provide energy-aware routing for routing hole detour. Simulation results demonstrate that EDGR exhibits higher energy efficiency, and has moderate performance improvements on network lifetime, packet delivery ratio, and delivery delay, compared to other geographic routing protocols in WSNs over a variety of communication scenarios passing through routing holes. The proposed EDGR is much applicable to resource-constrained WSNs with routing holes.
73 citations
TL;DR: A routing protocol based on genetic algorithm for a middle layer oriented network in which the network consists of several stations that are responsible for receiving data and forwarding the data to the sink and three methods are introduced for effective cope with the expansion of network scale problem.
Abstract: Energy saving and effective utilization are an essential issue for wireless sensor network. Most previous cluster based routing protocols only care the relationship of cluster heads and sensor nodes but ignore the huge difference costs between them. In this paper, we present a routing protocol based on genetic algorithm for a middle layer oriented network in which the network consists of several stations that are responsible for receiving data and forwarding the data to the sink. The amount of stations should be not too many and not too few. Both cases will cause either too much construction cost or extra transmission energy consumption. We implement five methods to compare the performance and test the stability of our presented methods. Experimental results demonstrate that our proposed scheme reduces the amount of stations by 36.8 and 20% compared with FF and HL in 100-node network. Furthermore, three methods are introduced to improve our proposed scheme for effective cope with the expansion of network scale problem.
66 citations
TL;DR: This work proposes a novel routing protocol inspired by the cuckoo search method that compares with the routing protocol ad hoc on-demand distance vector, destination sequence distance vector and the bio-inspired routing protocol AntHocNet in terms of the quality of service parameters.
Abstract: Mobile ad hoc networks (MANETs) are becoming an emerging technology that offer several advantages to users in terms of cost and ease of use. A MANET is a collection of mobile nodes connected by wireless links that form a temporary network topology that operates without a base station and centralized administration. Routing is a method through which information is forwarded from a transmitter to a specific recipient. Routing is a strategy that guarantees, at any time, the connection between any two nodes in a network. In this work, we propose a novel routing protocol inspired by the cuckoo search method. Our routing protocol is implemented using Network simulator 2. We chose Random WayPoint model as our mobility model. To validate our work, we opted for the comparison with the routing protocol ad hoc on-demand distance vector, destination sequence distance vector and the bio-inspired routing protocol AntHocNet in terms of the quality of service parameters: packet delivery ratio and end-to-end delay (E2ED).
38 citations
TL;DR: A fuzzy logic-based reliable routing protocol (FRRP) is proposed for MANETs which selects stable routes using fuzzy logic and is able to optimize system efficiency.
Abstract: MANET (mobile ad-hoc network) includes a set of wireless mobile nodes which communicate with one another without any central controls or infrastructures and they can be quickly implemented in the operational environment. One of the most significant issues in MANETs is concerned with finding a secure, safe and short route so that data can be transmitted through it. Although several routing protocols have been introduced for the network, the majority of them just consider the shortest path with the fewest number of hops. Hop criterion is considered for simple implementation and it is reliable in dynamic environments; however, queuing delay and connection delay in the intermediate nodes are not taken into consideration for selecting route in this criterion. In this paper, a fuzzy logic-based reliable routing protocol (FRRP) is proposed for MANETs which selects stable routes using fuzzy logic. It is able to optimize system efficiency. The score allocated to routes are based on four criteria: accessible bandwidth, the amount of energy of battery, the number of hops and the degree of dynamicity of nodes. The simulation results obtained from OPNET simulator version 10.5 indicate that the proposed protocol, in comparison with ad hoc on-demand distance vector (AODV) and fuzzy-based on-demand routing protocol (FBORP), was able to better improve packet delivery rate, average end-to-end delay and throughput.
35 citations
TL;DR: A new RPL-based routing protocol, termed as directional mutation ant colony optimization-based cognitive RPL (DMACO-RPL), for CR-enabled AMI networks, which utilizes a global optimization algorithm to select the best route from the whole network.
Abstract: Advanced metering infrastructure (AMI) networks, which are an integral component of the smart grid ecosystem, are practically deployed as a static multihop wireless mesh network. Recently, routing solutions for AMI networks have attracted a lot of attention in the literature. On the other hand, it is expected that the use of cognitive radio (CR) technology for AMI networks will be indispensable in near future. This paper investigates a global optimization-based routing protocol for enhancing quality of service in CR-enabled AMI networks. In accordance with practical requirements of smart grid applications, we propose a new RPL-based routing protocol, termed as directional mutation ant colony optimization-based cognitive RPL (DMACO-RPL), for CR-enabled AMI networks. This protocol utilizes a global optimization algorithm to select the best route from the whole network. In addition, DMACO-RPL explicitly protects primary (licensed) users while meeting the utility requirements of the secondary network. System-level simulations demonstrate that the proposed protocol enhances the performance of existing RPL-based routing protocols for CR-enabled AMI networks.
31 citations
TL;DR: The proposed energy-efficient data sensing and routing scheme (EEDSRS) in unreliable energy-harvesting wireless sensor network is developed and the experimental results demonstrate that the proposed EEDSRS is very promising and efficient.
Abstract: Energy-harvesting wireless sensor network (WSN) is composed of unreliable wireless channels and resource-constrained nodes which are powered by solar panels and solar cells. Energy-harvesting WSNs can provide perpetual data service by harvesting energy from surrounding environments. Due to the random characteristics of harvested energy and unreliability of wireless channel, energy efficiency is one of the main challenging issues. In this paper, we are concerned with how to decide the energy used for data sensing and transmission adaptively to maximize network utility, and how to route all the collected data to the sink along energy-efficient paths to maximize the residual battery energy of nodes. To solve this problem, we first formulate a heuristic energy-efficient data sensing and routing problem. Then, unlike the most existing work that focuses on energy-efficient data sensing and energy-efficient routing respectively, energy-efficient data sensing and routing scheme (EEDSRS) in unreliable energy-harvesting wireless sensor network is developed. EEDSRS takes account of not only the energy-efficient data sensing but also the energy-efficient routing. EEDSRS is divided into three steps: (1) an adaptive exponentially weighted moving average algorithm to estimate link quality. (2) an distributed energetic-sustainable data sensing rate allocation algorithm to allocate the energy for data sensing and routing. According to the allocated energy, the optimal data sensing rate to maximize the network utility is obtained. (3) a geographic routing with unreliable link protocol to route all the collected data to the sink along energy-efficient paths. Finally, extensive simulations to evaluate the performance of the proposed EEDSRS are performed. The experimental results demonstrate that the proposed EEDSRS is very promising and efficient.
30 citations
TL;DR: Optimal multimodal routing (OMR) as mentioned in this paper makes distributed decisions about the flow in each link and over each technology, at any given time, in order to advance a packet toward its destination.
Abstract: While acoustic communications are still considered the most prominent technology to communicate under water, other technologies are being developed based, e.g., on optical and radio-frequency electromagnetic waves. Each technology has its own advantages and drawbacks: for example, acoustic signals achieve long communication ranges at order-of-kbit/s rates, whereas optical signals offer order-of-Mbit/s transmission rates, but only over short ranges. Such diversity can be leveraged by multimodal systems, which integrate different technologies and provide the intelligence required to decide which one should be used at any given time. In this paper, we address a fundamental part of this intelligence by proposing optimal multimodal routing (OMR), a novel routing protocol for underwater networks of multimodal nodes. OMR makes distributed decisions about the flow in each link and over each technology, at any given time, in order to advance a packet toward its destination; in doing so, it prevents bottlenecks and allocates resources fairly to different nodes. We analyze the performance of OMR via simulations and in a field experiment. The results show that OMR successfully leverages all technologies to deliver data, even in the presence of imperfect topology information. To permit the reproduction of our results, we share our simulation code.
27 citations
TL;DR: This work proposes a light-weight time series based routing metric prediction method to deal with the high communication cost incurred by collecting the latest routing metrics between nodes and achieves 30% more Packet Delivery Ratio compared to the traditional AODV protocol.
20 citations
TL;DR: This work proposes an improved BP algorithm called sojourn-time-based BP (STBP), which effectively improves the end-to-end delay while ensuring throughput optimality and analyzes the network stability with delay considerations and proves the throughput Optimality of the STBP in multihop networks.
Abstract: Although the back-pressure (BP) algorithm has been proven to be a throughput-optimal policy for traffic scheduling and routing in wireless networks, the optimal control of delays in the BP algorithm remains an open problem, especially for conventional multihop networks. To enhance the delay performance, we proposed an improved BP algorithm called sojourn-time-based BP (STBP) by introducing a novel delay metric called the sojourn time backlog (STB). The STB considers the queue length and accumulated packet delays comprehensively. It provides more pressure to push forward flows suffering from greater delays. Based on this new metric, the calculation of the routing weight for each packet is determined for maximizing the difference of the STB in the routing process. The proposed routing algorithm is robust and distributed, and does not require any prior knowledge of network connections and load conditions. We analyze the network stability with delay considerations and prove the throughput optimality of the STBP in multihop networks. Simulation results reveal that the enhanced algorithm effectively improves the end-to-end delay while ensuring throughput optimality.
19 citations
TL;DR: Two protocols are proposed in order to optimally utilize the constrained network resources and reliably detect high-quality links and Signal Strength and Congestion Avoidance protocol (SSCA).
Abstract: During the last two decades, there has been a tremendous growth in the use of MANETs, not only due to the development of the technology but also due to their high flexibility. MANETs have challenges and limitations and among the major challenge is the routing process because of high dynamic topology and distributed nature. This is the main reason for quick depletion of network resources. Thus, there is a need to develop a routing protocol to fulfill various application requirements and enhance routing paths according to the topology change. In this paper, two protocols are proposed in order to optimally utilize the constrained network resources and reliably detect high-quality links. They are Hybrid Geo-cast Routing (HGR) protocol and Signal Strength and Congestion Avoidance protocol (SSCA). The optimal and adaptive HGR protocol utilizes geographical location information to limit search area during route discovery process by including only promising search paths to minimize control overhead. Meanwhile, adaptive SSCA uses SSCA mechanism in order to enhance link and node quality detection and reduce packet drop. The experimental results show that the proposed HGR protocol is able to reduce up to 46.67% control overhead. Meanwhile, the proposed adaptive SSCA protocol reduces packet drop to 71.20%.
TL;DR: The authors propose a novel MEO/LEO satellite network architecture that construct effective inter-satellite links and present a network coding-based multi-path routing algorithm to deliver traffic through the hybrid satellite network.
Abstract: Satellite networks are capable of contenting a variety of data transmission needs of users in geographically diverse locations throughout the world. Multi-layered satellite networks (MLSNs) can construct efficient communications networks due to their extensive coverage and high network capacity. However, throughput degradation and severe end-to-end delay could occur in MLSNs because of the traffic congestion. To resolve these problems, the authors first propose a novel MEO/LEO satellite network architecture that construct effective inter-satellite links. Then the authors present a network coding-based multi-path routing algorithm to deliver traffic through the hybrid satellite network. The analysis of characteristics of the proposed scheme are addressed by performance evaluations in simulation.
TL;DR: The WTR mechanism uses Dijkstra’s shortest path routing algorithm in which the weights are deliberated using certain parameters such as node-distance, packet-loss and trust value of each node which is computed using social impact theory optimizer.
Abstract: In this paper, we have exploited the weight trusted routing (WTR) mechanism to detect and eliminate the malicious nodes involved during the routing path formation in smart-home environments where the routing between the communicating entities is performed through the mesh architecture. Further, to provide a secure communication against malicious behavior of nodes, the proposed mechanism uses Dijkstra’s shortest path routing algorithm in which the weights are deliberated using certain parameters such as node-distance, packet-loss and trust value of each node which is computed using social impact theory optimizer. Moreover, we have presented the network performance trade-off caused by secure path formation with conventional method and have proposed the WTR mechanism for eliminating the potential issues such as packet-loss ratio, end-to-end delay and network throughput. The commercial simulator NS2 is used to simulate and compare the network metrics for both conventional as well as proposed approach and is validated with experimental results over end-to-end delay and message delivery ratio against reported literature.
TL;DR: A new routing performance metric, namely, network pressure, is proposed and, based on network pressure and Divide-Conquer method, high performance routing could be achieved.
Abstract: Due to the huge routing algorithm search space for 2D mesh based Network-on-Chip (NoC), Divide-Conquer method is presented to effectively explore the search space. When using Divide-Conquer method, a large number of routing algorithms will be created. In order to get the final results in an acceptable time, a precise metric is needed to measure routing performance and discard the poor performance routings. In this paper, we propose a new routing performance metric, namely, network pressure. Network pressure has the following three advantages: (1) it could measure the whole network congestion state; (2) network pressure of a network and that of its partial component is highly related, under the same routing; (3) it is closely related with routing performance. Based on network pressure and Divide-Conquer method, high performance routing could be achieved. The obtained routing is called suboptimal routing due to the following two reasons: (1) there is only a little gap between its performance and that of the fully adaptive routings under both transpose1 and transpose2 traffics. (2) the search space of routing algorithms is systematically and widely exploited.
TL;DR: The overall performance of TSMR surpasses that of others for packet delivery ratio, end-to-end delay, control overhead, memory consumption, and power consumption regardless of network size, number of sessions, and traffic flow.
Abstract: Single-path routing is widely used in wireless networks due to low resource consumption. However, it is vulnerable to link failure because such a failure may adversely affect an entire path. To overcome this, multipath routing has been proposed providing fault-tolerance. In this paper, we propose a novel multipath routing protocol called traffic-aware stateless multipath routing (TSMR) based on an overlaid tree topology comprising two topologies, namely, bounded degree tree (BDT) and root-oriented directional tree (RODT). BDT is strong on reducing routing overhead, and RODT is resilient against lossy links. By synergistically overlaying them, TSMR dynamically selects the local optimal path according to the given traffic flow and the failure on the primary path. In particular, TSMR enables stateless and low overhead routing despite multipath routing by keeping only one-hop neighbors to maintain multiple paths. To evaluate TSMR, we conducted simulations with a shadowing model reflecting lossy links, and compared with single and multipath routing protocols, such as ZTR, STR, AODV, and RPL. The simulation results show that the overall performance of TSMR surpasses that of others for packet delivery ratio, end-to-end delay, control overhead, memory consumption, and power consumption regardless of network size, number of sessions, and traffic flow.
TL;DR: The encompassing simulations suggest that the ER3 outperforms the existing routing protocols on the basis of energy efficiency, low latency and high packet delivery ratio.
Abstract: Sensor networks designed especially for the multimedia applications require high data rate and better Quality of Service (QoS). Offering a reliable and energy efficient routing technique in a harsh and complex three-dimensional (3-D) environment for multimedia applications is a challenging job. Geo-routing and geometric routing have been efficient routing schemes for two-dimensional (2-D), but are unable to work properly for 3-D sensor networks. In order to enhance the resilience to link the dynamics in the 3-D sensor network, in this research an Enhanced Reliable Reactive Routing (ER3) is proposed. ER3 is an advancement to the existing reactive routing schemes, to provide energy efficient and reliable routing of data packets in the complex 3-D sensor networks for multimedia applications. The major attraction of ER3 is its backoff scheme, which occurs in the route discovery phase. In backoff scheme robust pilot paths formed between the source and destination are calculated to enable cooperative forwarding of the data packets. The data packets in ER3 are forwarded greedily to the destination from the source and doesn’t require any prior location information of the nodes. The encompassing simulations suggest that the ER3 outperforms the existing routing protocols on the basis of energy efficiency, low latency and high packet delivery ratio.
TL;DR: JRS-S and JRS-M algorithms are proposed, which utilize both route discovery and resource allocation at the same time, in order to maximize capacity of the wireless mesh network in the cloud computing and can improve system capacity by efficiently distributing a gateway load.
Abstract: In recent years, building the cloud based on wireless mesh networks as well as wired networks is rapidly increased for processing the big data. However, existing scheduling and routing protocols cannot support processing the big data efficiently in the cloud, because the each flow path is determined before the data are transmitted based on some routing strategies in the wireless mesh networks. Currently, an important factor that should be considered is that the link capacity between mesh routers can be changed based on the current interference of the flow of other mesh routers. In general, network availability is also influenced by the interference related to the other layers in the protocol stack. In this paper, we study wireless mesh networks and propose JRS-S and JRS-M algorithms, which utilize both route discovery and resource allocation at the same time, in order to maximize capacity of the wireless mesh network in the cloud computing. Our algorithms for each flow use a cross-layer design method based on numerical modeling in order to adaptively control data scheduling at the link layer and find a high data rate path with minimum interference at the network layer. We analyze the optimal capacity of the wireless mesh networks for maximizing network utilization using a numerical solution tool. Through analysis, we also verify that our algorithms can improve system capacity by efficiently distributing a gateway load and that it can enhance the system availability.
TL;DR: A new routing protocol called TwoD-IP routing is proposed to facilitate enterprise network management and can achieve flexible management by providing different views on the same network for different users.
Abstract: With the development of the Internet, people put more demands on networks. Among different networks, enterprise network faces more challenges, because of its large scale and diverse goals. Configuration of enterprise network is always daunting for network operators. In this paper, we propose a new routing protocol called TwoD-IP routing to facilitate enterprise network management. With TwoD-IP routing, we can achieve flexible management by providing different views on the same network for different users. We design the routing protocol algorithm, and implement it on a quagga-based router. Finally, we evaluate our mechanism using simulations with BRITE generated topologies. The results show that our mechanism can greatly reduce the network configuration complexities.
01 Jan 2018
TL;DR: Three routing protocols, AOMDV, MOLSR, and MHRP, are compared in terms of their performance in WMN to result in reduction of monetary investment and cost of operation.
Abstract: The WMNs are coming up as a new networking trend for setting up a wireless networking infrastructure in metropolitan areas. Network operators prefer WMN because of easy installation and fast deployment of it. It may also result in reduction of monetary investment and cost of operation. The routing in WMNs is challenging task because of the unpredictable variations in the wireless environments. In this paper, three routing protocols, AOMDV, MOLSR, and MHRP, are compared in terms of their performance in WMN.
TL;DR: Comparison to earlier work shows that KDSR causes less computation complexity, less communication overhead and much less storage space even for large-scale WSNs.
Abstract: This article deals with a key distribution protocol to secure routing in large-scale Wireless Sensor Networks WSNs and proposes a new protocol called KDSR. The authors' protocol has two originalities: to provide a secure network structure for large-scale WSNs, and to use lightweight local process to share efficiently the Local Broadcast Keys, the Pairwise Keys and the Global Broadcast Key. These keys are useful to secure several communication patterns in WSNs: one-to-many, one-to-one and one-to-all. Security analyses show that KDSR can withstand several attacks against WSNs. Through fast node revocation process, KDSR offers a good resilience against node capture. Immunity against MiM and replay attacks are well checked with the AVISPA tools. The experimentations are done on real TelosB motes and through the TOSSIM simulator. Simulation results confirm that KDSR is scalable, provides a good key connectivity and a good resilience. Comparison to earlier work shows that KDSR causes less computation complexity, less communication overhead and much less storage space even for large-scale WSNs.
TL;DR: In this paper, compressed sensing is used to reduce routing traffic overhead at nodes which have greater processing capabilities and no power consumption limitations and it is shown that a proper choice of weighting coefficients in the sampling process can improve detection performance.
Abstract: In table routing protocols such as link state routing, every node in the network periodically broadcasts its link state and the state of its neighbors. These routing updates result in the transmission of a large number of packets. Some of these packets contain correlated or even redundant data which could be compressed if there is central management in the network. However, in autonomous networks, each node acts as a router, in which case central coordination is not possible. In this paper, compressed sensing is used to reduce routing traffic overhead. This can be done at nodes which have greater processing capabilities and no power consumption limitations such as backbone nodes in wireless mesh networks. A method is proposed to select a subset of nodes and thus a subset of links to probe their state. The sensed states are encoded to generate a low dimension sampled vector. This compressed link state vector is broadcast to the entire network. Nodes can then reconstruct link states from this vector using side information. Performance results are presented which demonstrate accurate anomaly detection while adapting to topology changes. Further, it is shown that a proper choice of weighting coefficients in the sampling process can improve detection performance.
01 Jan 2018
TL;DR: In this chapter, an introduction to networking and network routing is presented, covering basics on addressing and the protocol stack.
Abstract: In this chapter, we present an introduction to networking and network routing. We cover basics on addressing and the protocol stack. We also discuss varied ways the term “architecture" is used, and how this relates to network routing. Furthermore, the global telephone network and communication technologies are briefly presented.