Showing papers on "Geographic routing published in 2018"

Energy-Aware Dual-Path Geographic Routing to Bypass Routing Holes in Wireless Sensor Networks

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.

Analysis of Cross-Layer Design of Quality-of-Service Forward Geographic Wireless Sensor Network Routing Strategies in Green Internet of Things

Abstract: Wireless sensor networks suffer from some limitations such as energy constraints and the cooperative demands essential to perform multi-hop geographic routing for Internet of things (IoT) applications. Quality of Service (QoS) depends to a great extent on offering participating nodes an incentive for collaborating. This paper presents a mathematical model for a new-generation of forwarding QoS routing determination that enables allocation of optimal path to satisfy QoS parameters to support a wide range of communication-intensive IoT’s applications. The model is used to investigate the effects of multi-hop communication on a traffic system model designed with a Markov discrete-time $M/M/1$ queuing model, applicable to green deployment of duty-cycle sensor nodes. We present analytical formulation for the bit-error-rate, and a critical path-loss model is defined to the specified level of trust among the most frequently used nodes. Additionally, we address the degree of irregularity parameter for promoting adaptation to geographic switching with respect to two categories of transmission in distributed systems: hop-by-hop and end-to-end retransmission schemes. The simulations identified results for the average packet delay transmission, the energy consumption for transmission, and the throughput. The simulations offer insights into the impact of radio irregularity on the neighbor-discovery routing technique of both schemes. Based on the simulation results, the messages en-coded with non-return-to-zero have more green efficiency over multi-hop IoT (without loss of connectivity between nodes) than those encoded with the Manchester operation. The findings presented in this paper are of great help to designers of IoT.

QERP: Quality-of-Service (QoS) Aware Evolutionary Routing Protocol for Underwater Wireless Sensor Networks

Abstract: Quality-of-service (QoS) aware reliable data delivery is a challenging issue in underwater wireless sensor networks (UWSNs). This is due to impairments of the acoustic transmission caused by excessive noise, extremely long propagation delays, high bit error rate, low bandwidth capacity, multipath effects, and interference. To address these challenges, meet the commonly used UWSN performance indicators, and overcome the inefficiencies of the existing clustering-based routing schemes, a novel QoS aware evolutionary cluster based routing protocol (QERP) has been proposed for UWSN-based applications. The proposed protocol improves packet delivery ratio, and reduces average end-to-end delay and overall network energy consumption. Our comparative performance evaluations demonstrate that QERP is successful in achieving low network delay, high packet delivery ratio, and low energy consumption.

Energy-Aware Mobile Edge Computing and Routing for Low-Latency Visual Data Processing

Abstract: New paradigms such as Mobile Edge Computing (MEC) are becoming feasible for use in, e.g., real-time decision-making during disaster incident response to handle the data deluge occurring in the network edge. However, MEC deployments today lack flexible IoT device data handling such as handling user preferences for real-time versus energy-efficient processing. Moreover, MEC can also benefit from a policy-based edge routing to handle sustained performance levels with efficient energy consumption. In this paper, we study the potential of MEC to address application issues related to energy management on constrained IoT devices with limited power sources, while also providing low-latency processing of visual data being generated at high resolutions. Using a facial recognition application that is important in disaster incident response scenarios, we propose a novel “offload decision-making” algorithm that analyzes the tradeoffs in computing policies to offload visual data processing (i.e., to an edge cloud or a core cloud) at low-to-high workloads. This algorithm also analyzes the impact on energy consumption in the decision-making under different visual data consumption requirements (i.e., users with thick clients or thin clients). To address the processing-throughput versus energy-efficiency tradeoffs, we propose a “Sustainable Policy-based Intelligence-Driven Edge Routing” algorithm that uses machine learning within Mobile Ad hoc Networks. This algorithm is energy aware and improves the geographic routing baseline performance (i.e., minimizes impact of local minima) for throughput performance sustainability, while also enabling flexible policy specification. We evaluate our proposed algorithms by conducting experiments on a realistic edge and core cloud testbed in the GENI Cloud infrastructure, and recreate disaster scenes of tornado damages within simulations. Our empirical results show how MEC can provide flexibility to users who desire energy conservation over low latency or vice versa in the visual data processing with a facial recognition application. In addition, our simulation results show that our routing approach outperforms existing solutions under diverse user preferences, node mobility, and severe node failure conditions.

QoS-based routing in Wireless Body Area Networks: a survey and taxonomy

Abstract: Wireless Body Area Network (WBAN) constitutes a set of sensor nodes responsible for monitoring human physiological activities and actions. The increasing demand for real time applications in such networks stimulates many research activities in quality-of-service (QoS) based routing for data delivery. Designing such scheme of critical events while preserving the energy efficiency is a challenging task due to the dynamic of the network topology, severe constraints on power supply and limited in computation power and communication bandwidth. The design of QoS-based routing protocols becomes an essential part of WBANs and plays an important role in the communication stacks and has significant impact on the network performance. In this paper, we classify, survey, model and compare the most relevant and recent QoS-based routing protocols proposed in the framework of WBAN. A novel taxonomy of solutions is proposed, in which the comparison is performed with respect to relevant criteria. An analytical model is proposed in order to compare the performances of all the solutions. Furthermore, we provide a study of adaptability of the surveyed protocols related to the healthcare sector.

Real-Time Intersection-Based Segment Aware Routing Algorithm for Urban Vehicular Networks

Abstract: High vehicular mobility causes frequent changes in the density of vehicles, discontinuity in inter-vehicle communication, and constraints for routing protocols in vehicular ad hoc networks (VANETs). The routing must avoid forwarding packets through segments with low network density and high scale of network disconnections that may result in packet loss, delays, and increased communication overhead in route recovery. Therefore, both traffic and segment status must be considered. This paper presents real-time intersection-based segment aware routing (RTISAR), an intersection-based segment aware algorithm for geographic routing in VANETs. This routing algorithm provides an optimal route for forwarding the data packets toward their destination by considering the traffic segment status when choosing the next intersection. RTISAR presents a new formula for assessing segment status based on connectivity, density, load segment, and cumulative distance toward the destination. A verity period mechanism is proposed to denote the projected period when a network failure is likely to occur in a particular segment. This mechanism can be calculated for each collector packet to minimize the frequency of RTISAR execution and to control the generation of collector packets. As a result, this mechanism minimizes the communication overhead generated during the segment status computation process. Simulations are performed to evaluate RTISAR, and the results are compared with those of intersection-based connectivity aware routing and traffic flow-oriented routing. The evaluation results provided evidence that RTISAR outperforms in terms of packet delivery ratio, packet delivery delay, and communication overhead.

Energy Efficient Link-Delay Aware Routing in Wireless Sensor Networks

Abstract: This paper investigates the problem of energy consumption in wireless sensor networks. Wireless sensor nodes deployed in harsh environment where the conditions change drastically suffer from sudden changes in link quality and node status. The end-to-end delay of each sensor node varies due to the variation of link quality and node status. On the other hand, the sensor nodes are supplied with limited energy and it is a great concern to extend the network lifetime. To cope with those problems, this paper proposes a novel and simple routing metric, predicted remaining deliveries (PRD), combining parameters, including the residual energy, link quality, end-to-end delay, and distance together to achieve better network performance. PRD assigns weights to individual links as well as end-to-end delay, so as to reflect the node status in the long run of the network. Large-scale simulation results demonstrate that PRD performs better than the widely used ETX metric as well as other two metrics devised recently in terms of energy consumption and end-to-end delay, while guaranteeing packet delivery ratio.

BERA: a biogeography-based energy saving routing architecture for wireless sensor networks

Abstract: Biogeography-based optimization (BBO) is a relatively new paradigm for optimization which is yet to be explored to solve complex optimization problems to prove its full potential. In wireless sensor networks (WSNs), optimal cluster head selection and routing are two well-known optimization problems. Researchers often use hierarchal cluster-based routing, in which power consumption of cluster heads (CHs) is very high due to its extra functionalities such as receiving and aggregating the data from its member sensor nodes and transmitting the aggregated data to the base station (BS). Therefore, proper care should be taken while selecting the CHs to enhance the life of the network. After formation of the clusters, data to be routed to the BS in inter-cluster fashion for further enhancing the life of WSNs. In this paper, a biogeography-based energy saving routing architecture (BERA) is proposed for CH selection and routing. The biogeography-based CH selection algorithm is proposed with an efficient encoding scheme of a habitat and by formulating a novel fitness function that uses residual energy and distance as its metrics. The BBO-based routing algorithm is also proposed. The efficient encoding scheme of a habitat is developed, and its fitness function considers the node degree in addition to residual energy and distance. To exhibit the performance of BERA, it is extensively tested with some existing routing algorithms such as DHCR, Hybrid routing, EADC and some bio-inspired algorithms, namely GA and PSO. Simulation results confirm the superiority/competitiveness of the proposed algorithm over existing techniques.

Fog computing enabling geographic routing for urban area vehicular network

Abstract: Geographic routing scheme has received considerable attention recently. We present a position-based routing scheme called improved geographic routing (IGR) for the inter-vehicle communication in city environments. IGR uses the vehicular fog computing to make the best utilization of the vehicular communication and computational resources. IGR consists of two modes: (i) junction selection according to the distance to the destination and the vehicle density of each street, and (ii) an improved greedy forwarding strategy to transmit a data packet between two junctions. In the improved greedy forwarding mode, link error rate is considered in the path selection. Simulations are conducted to evaluate the performance of IGR. Simulation results show that IGR has a significant improvement in terms of the achieved packet rate and end-to-end delay.

On Caching and Routing in Information-Centric Networks

Abstract: With the exponential growth of content in recent years, users are primarily interested in obtaining particular content and are not concerned with the host housing the content. By treating content as a first class citizen, information- centric networks (ICN) seek to transform the Internet from a host-to-host communication model to a content-centric model. A key component of ICN is to cache content at storage-enabled routers. By caching content at in-network routers, network performance can be improved by delivering content from routers closer to the user and not from the origin servers (content custodians). In this article, we provide an overview of the state-of-the-art cache management and routing policies in ICN. We present a small comparison study of some state-of-the-art algorithms on a real Internet topology to help the reader appreciate how the different strategies compare against one another. Our simulation results demonstrate that it is hard to pick a winner among existing policies. We conclude the article with a discussion of open research questions.

Multi-metric geographic routing for vehicular ad hoc networks

Abstract: Maintaining durable connectivity during data forwarding in Vehicular Ad hoc Networks has witnessed significant attention in the past few decades with the aim of supporting most modern applications of intelligent transportation systems. Various techniques for next hop vehicle selection have been suggested in the literature. Most of these techniques are based on selection of next hop vehicles from fixed forwarding region with two or three metrics including speed, distance and direction, and avoid many other parameters of urban environments. In this context, this paper proposes a Multi-metric Geographic Routing (M-GEDIR) technique for next hop selection. It selects next hop vehicles from dynamic forwarding regions, and considers major parameters of urban environments including, received signal strength, future position of vehicles, and critical area vehicles at the border of transmission range, apart from speed, distance and direction. The performance of M-GEDIR is evaluated carrying out simulations on realistic vehicular traffic environments. In the comparative performance evaluation, analysis of results highlight the benefit of the proposed geographic routing as compared to the state-of-the-art routing protocols.

Energy-efficient data sensing and routing in unreliable energy-harvesting wireless sensor network

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.

Packet Routing in 3D Nanonetworks: A Lightweight, Linear-path Scheme

Abstract: Packet routing in nanonetworks requires novel approaches, which can cope with the extreme limitations posed by the nano-scale. Highly lossy wireless channels, extremely limited hardware capabilities and non-unique node identifiers are among the restrictions. The present work offers an addressing and routing solution for static 3D nanonetworks that find applications in material monitoring and programmatic property tuning. The addressing process relies on virtual coordinates from multiple, alternative anchor point sets that act as \emph{viewports}. Each viewport offers different address granularity within the network space, and its selection is optimized by a packet sending node using a novel heuristic. Regarding routing, each node can deduce whether it is located on the linear segment connecting the sender to the recipient node. This deduction is made using integer calculations, node-local information and in a stateless manner, minimizing the computational and storage overhead of the proposed scheme. Most importantly, the nodes can regulate the width of the linear path, thus trading energy efficiency (redundant transmissions) for increased path diversity. This trait can enable future adaptive routing schemes. Extensive evaluation via simulations highlights the advantages of the novel scheme over related approaches.

Integrating Localization and Energy-Awareness: A Novel Geographic Routing Protocol for Underwater Wireless Sensor Networks

Abstract: Underwater wireless sensor networks (UWSNs) are the enabling technology for a new era of underwater monitoring and actuation applications. While an efficient routing protocol for data packet delivery is crucial to UWSNs, design of such a protocol faces many challenges due to the characteristics of the acoustic channel used for communication. One of the challenges is high energy consumption by sensors in routing, which critically shortens the lifespan of the sensors involved in packet delivery. In this paper, we present a novel energy-efficient localization-based geographic routing protocol EEL, which uses location information and residual energy of sensor nodes to greedily forward data packets to sink nodes. EEL periodically updates the location information of nodes in an UWSN and effectively adapt to the dynamic topological changes of the network. EEL iterates through a list of candidate forwarding nodes by considering the NADV (Normalized Advancement) of these nodes that determines their transmission priority levels. Simulation results show that EEL can effectively locate sensor nodes while significantly improving the packet delivery ratio and reducing the energy consumption in a routing process as compared to other routing protocols used by UWSNs.

Geo-Routing Algorithms and Protocols for Power Line Communications in Smart Grids

Abstract: Making electric power grids smart is invariably linked to the implementation of an advanced communication infrastructure that is able to transport sensing, control and automation information timely, reliably and efficiently. Reusing the power line themselves to realize (part of) this infrastructure is an obvious choice that has a long and successful track record with power utilities. In this paper, we propose to make use of the fact that the nodes of a power line communications (PLCs) network are stationary to deliver messages fast and energy efficiently through routes consisting of a series of communication links. In particular, we exploit location information of PLC nodes to route a message along a favorable path. Such geographic or geo-routing is particularly apt for PLC networks with time-varying link qualities, where optimal routes will change with time. We present routing algorithms and protocols for unicast, broadcast, and multicast transmission that use network topology knowledge to determine the message path taking energy and delay constraints into account. We focus on the distribution domain of the power grid and propose decentralized solutions that use of information about the communication neighborhood of a node, which is acquired through proper signaling in the grid.

Learning for Robust Routing Based on Stochastic Game in Cognitive Radio Networks

Abstract: This paper studies the problem of spectrum-aware routing in a multi-hop, multi-channel cognitive radio network when malicious nodes in the secondary network attempt to block the path with mixed attacks. Based on the location and time-variant path delay information, we model the path discovery process as a non-cooperative stochastic game. By exploiting the structure of the underlying Markov Decision Process, we decompose the stochastic routing game into a series of stage games. For each stage game, we propose a distributed strategy learning mechanism based on stochastic fictitious play to learn the equilibrium strategies of joint relay-channel selection in the condition of both limited information exchange and potential routing-toward-primary attacks. We also introduce a trustworthiness evaluation mechanism based on a multi-arm bandit process for normal users to avoid relaying to the sink-hole attackers. Simulation results show that without the need of information flooding, the proposed algorithm is efficient in bypassing the malicious nodes with mixed attacks.

A Geographic Multicopy Routing Scheme for DTNs With Heterogeneous Mobility

Abstract: Previous geographic routing schemes in delay/disruption tolerant networks (DTNs) only consider the homogeneous scenario where nodal mobility is identical. Motivated by this gap, we turn to design a DTN based geographic routing scheme in heterogeneous scenario. Systematically, our target is achieved via two steps: 1) We first propose, “The-best-geographic-relay (TBGR)” routing scheme to relay messages via a limited number of copies, under the homogeneous scenario. We further overcome the local maximum problem of TBGR given a sparse network density, different from those efforts in dense networks like clustered wireless sensor networks. 2) We next extend TBGR for heterogeneous scenario, and propose “the-best-heterogeneity-geographic-relay (TBHGR)” routing scheme considering individual nodal visiting preference (referred to nonidentical nodal mobility). Extensive results under a realistic heterogeneous scenario show the advantage of TBHGR over literature works in terms of reliable message delivery, while with low routing overhead.

Radius-based multipath courier node routing protocol for acoustic communications

Abstract: Underwater wireless sensor networks (UWSNs) use acoustic waves to communicate in an underwater environment. Acoustic channels have various limitations such as low bandwidth, a higher end-to-end delay, and path loss at certain nodes. Considering the limitations of UWSNs, energy efficient communication and reliability of UWSNs have become an inevitable research area. The current research interests are to operate sensors for a longer time. The currently investigated research area towards efficient communication has various challenges, like flooding, multiple copies creation path loss and low network life time. Hence, it is different from previous work which solved certain challenges by measuring the depth, residual energy, and assigning hop-IDs to nodes. This study has proposed a novel scheme called radius-based courier node (RMCN) routing. RMCN uses radius-based architecture in combination with a cost function, track-ID, residual energy, and depth to forward data packets. The RMCN is specifically designed for long-term monitoring with higher energy efficiency and packet delivery ratio. The purpose of RMCN is to facilitate a network for longer periods in risky areas. The proposed routing scheme has been compared with depth-based routing and energy-efficient multipath grid-based geographic routing with respect to alive nodes left, end to end delay, delivery ratio and energy consumption.

Delay-Optimal Back-Pressure Routing Algorithm for Multihop Wireless 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.

Position adjustment–based location error–resilient geo‐opportunistic routing for void hole avoidance in underwater sensor networks

Abstract: This paper presents four routing protocols for Underwater Sensor Networks (USNs): Location Error–resilient Transmission Range adjustment–based protocol (LETR), Mobile Sink–based GEographic and Opportunistic Routing (MSGER), Mobile Sink–based LETR (MSLETR), and Modified MSLETR (MMS‐LETR). LETR considers transmission range levels for finding neighbor nodes. If a node fails to find any neighbor node within its defined maximum transmission range level, it recovers from communication void regions using depth adjustment technology. MSGER and MSLETR avoid depth and transmission range adjustment and overcome the problem of communication void regions using MSs, whereas MMS‐LETR takes into account noise attenuation at various depth levels, elimination of retransmissions using multi‐path communication and load balancing. The performance of our proposed protocols is evaluated through simulations using different parameters. The simulation results show that MSS‐LETR supersedes all counterpart schemes in terms of packet loss ratio. LETR significantly improves network performance in terms of energy consumption, packet loss ratio, fraction of void nodes, and the total amount of depth adjustment.

Scalable Deadlock-Free Deterministic Minimal-Path Routing Engine for InfiniBand-Based Dragonfly Networks

Abstract: Dragonfly topologies are gathering great interest nowadays as one of the most promising interconnect options for High-Performance Computing (HPC) systems. However, Dragonflies contain physical cycles that may lead to traffic deadlocks unless the routing algorithm prevents them properly. In general, existing deadlock-free routing algorithms, either deterministic or adaptive, proposed for Dragonflies, use Virtual Channels (VCs) to prevent cyclic dependencies. However, these topology-aware algorithms are difficult to implement, or even unfeasible, in systems based on the InfiniBand (IB) architecture, which is nowadays the most widely used network technology in HPC systems. This is due to some limitations in the IB specification, specifically regarding the way Virtual Lanes (VLs), which are considered as similar to VCs, can be assigned to traffic flows. Indeed, none of the routing engines currently available in the official releases of the IB control software has been specifically proposed for Dragonflies. In this paper, we present a new deterministic, minimal-path routing for Dragonfly that prevents deadlocks using VLs according to the IB specification, so that it can be straightforwardly implemented in IB-based networks. We have called this proposal D3R (Deterministic Deadlock-free Dragonfly Routing). Specifically, D3R maps each route to a single, specific VL depending on the destination group, and according to a specific order, so that cyclic dependencies (so deadlocks) are prevented. D3R is scalable as it requires only 2 VLs to prevent deadlocks regardless of network size, i.e., fewer VLs than the required by the deadlock-free routing engines available in IB that are suitable for Dragonflies. Alternatively, D3R achieves higher throughput if an additional VL is used to reduce internal contention in the Dragonfly groups. We have implemented D3R as a new routing engine in OpenSM, the control software including the subnet manager in IB. We have evaluated D3R by means of simulation and by experiments performed in a real IB-based cluster, the results showing that, in general, D3R outperforms other routing engines.

Network coding-based multi-path routing algorithm in two-layered satellite networks

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.

An effective data fusion-based routing algorithm with time synchronization support for vehicular wireless sensor networks

Abstract: In the field of vehicular wireless sensor networks-based structural health monitoring, the structural damage identification is achieved by two structural features, namely natural frequencies and mode shapes. The kind of data fusion-based routing algorithm in specific applications needs to meet time synchronization requirements and meet certain constraints, such as the single-hop communication between cluster head node and each node in cluster, the overlap between different clusters and so on. To meet the special constraints for data fusion-based routing algorithm in structural health monitoring, this paper proposed a new method based on an improved flooding time synchronization protocol, which is called time synchronization and enhanced greedy algorithm based on D(v) (TSDEGA) routing algorithm. The TSDEGA method can achieve the minimum connected cover by node’s own degree D(v), and it can also meet the structural health monitoring routing constraints. The simulation experiments show that TSDEGA has better energy resistance and longer network lifetime, and it is superior to the traditional greedy algorithms. The proposed algorithm can effectively eliminate interference of outliers and improve the accuracy in order to meet time synchronization requirements in structural health monitoring applications.

Low overhead hybrid geographic-based routing algorithms with smart partial flooding for 3D ad hoc networks

Abstract: One known design for routing algorithms in mobile ad hoc networks is to use flooding. But, these algorithms are usually suffer from high overhead. Another common design is to use the nodes geographic locations to take routing choices. Current geographical routing algorithms usually address the routing environment in 2D space. However, in real life, nodes could be located in 3D space. To benefit from the advantages of both techniques we propose several 3D new routing algorithms that maximize the packets delivery rate and minimize the overhead. Our first set of algorithms (SPF: smart partial flooding) uses the nodes location to do the flooding in the direction of the destination over a sub-graph of the original dense graph. The second set (Progress–SPF) uses geographical routing to progress as much as possible to the destination, if its not possible, SPF is used over a sub-graph extracted locally. The 3rd set (Progress–SPF–Progress) used geographical routing to progress to the destination, if the progress is not possible, SPF is used over a sub-graph for one step only and then the algorithm goes back to the geographical routing. We evaluate our algorithms and compare them with current routing algorithms. The simulation results show a significant improvement in delivery rate up to $$100\%$$ compared to $$70\%$$ and a huge reduction in overall traffic around $$60\%$$ .

Load balanced and constant stretch routing in the vicinity of holes in WSNs

Abstract: Because of its simplicity and scalability, geographic routing is a popular approach in wireless sensor networks, which can achieve a near-optimal routing path in the networks without holes (i.e., regions without working sensors). With the occurrence of holes, however, geographic routing faces the problems of load imbalance and routing path enlargement. In the literature, several proposals have attempted to fix these issues, but the majority of them considers only the cases when both the source and the destination stay fairly far from the holes. Recently, a few work has been proposed to tackle the problem of routing in the vicinity of routing holes. However, none of them addresses the two problems (i.e., load imbalance and routing path enlargement) concurrently, and none of them can solve the problem of load imbalance thoroughly. In this paper, we introduce a novel approach in dealing with routing in the vicinity of holes, that is the first to target and solve both the load imbalance and path enlargement problems. The theoretical analysis proves that the routing path stretch of our proposed protocol can be controlled to be as small as 1 + e (for any predefined e> 0) and the simulation experiments show that our protocol strongly outperforms the existing protocols in terms of load balancing.

Resource Allocation and Multisession Routing Algorithms in Coordinated Multipoint Wireless Communication Networks

Abstract: In heterogeneous wireless networks, coordinated multipoint technology facilitates coordination and mutual cooperation among various types of networks and applications. The resource requirements of various applications differ considerably under the constraint of limited resources so that the allowable delay is considered. This study considered a centralized management scheme involving fourth-generation (4G) mobile networks Evolved Node B, access points, and back-end coordinated servers. The operator controls the flow and performs routing selection procedures through long-term evolution advanced and Wi-Fi in accordance with the 5G wireless networks. The problem was constructed as a mathematical programming model. A Lagrangian relaxation (LR) approach was adopted to maximize the revenue minus the penalty costs as objective to evaluate the resource allocation, tolerable delay, and multisession routing algorithm. The primal problem was decomposed into seven independent subproblems through LR procedures, and the combination of a subgradient method and a routing algorithm was used to obtain approximate solutions. A novel algorithm for flow control involving multisession routing is proposed for handling resource allocation. The algorithm involving a near-optimal approach was designed to solve the insufficient resource problem. The solution can be used by operators for improving resource utilization in next-generation wireless networks.

Enhanced Adaptive Geographic Opportunistic Routing with Interference Avoidance Assisted with Mobile Sinks for Underwater Wireless Sensor Network

Abstract: Acoustic communication in Underwater Wireless Sensor Networks (WSNs) is limited due to distinctive attributes including communication channel high latency, multi-path fading and exponential degrading on signal due to dynamic noise characteristics. Inappropriate selection of forwarder node leads to dramatic death due to inefficient, unbalanced energy depletion that results in creation of void hole for neighboring nodes. In most of scenarios, forwarder nodes are over penalized by selecting same node all the time. Enhanced adaptive mechanism is proposed to cater over penalization of forwarder node by adaptively lowering the priority of node gradually along with residual energy. Proposed routing protocols are based on geoopportunistic routing paradigm based on interference avoidance which is assisted by mobile sinks. More specific and unified routing decisions are formed by dividing the whole network field into cubes. Forwarder nodes are elected on geographic location of neighboring cubes depending on packet delivery probability. Void node recovery mechanism is also proposed and evaluated by deploying mobile sink to directly gather data from void nodes. Extensive simulations are performed to evaluate the proposed work. Simulations prove that proposed work significantly increases packet delivery and decrease fraction of void nodes.