Dynamic multi-objective routing algorithm: a multi-objective routing algorithm for the simple hybrid routing protocol on wireless sensor networks

Popularity of Mobile Wireless Sensor Network (MWSN) has increased tremendously due to the ability to connect the physical world with the virtual world. In MWSN, Sensor nodes move freely in a target area without the need of any special infrastructure. MWSN has attracted many researchers as it has introduced unique challenges in aspects like resource management, coverage, routing protocols, security in many applications such as target tracking in military applications, detection of catastrophic events, environment monitoring, health applications etc. Due to mobility, routing process in MWSN has become more complicated as connections in the network can change dynamically. This paper proposes a Mobility-Aware Multi-Objective Hybrid Routing Algorithm (MMOHRA) for Wireless Sensor Network (WSN). MMOHRA selects the best route and forwards the data packets from source to sink using multiple metrics such as Average Energy consumption, Control Overhead, Reaction Time, LQI, and HOP Count. Performance of MMOHRA is compared with Simple Hybrid Routing Protocol (SHRP) and Dynamic Multi-objective Routing Algorithm (DyMORA) using metrics such as Average Energy Consumption, Packet Delivery Ratio, and Jitter. MMOHRA improves the Average Energy Consumption (AEC) by a factor of 14.1% as compared with SHRP and 8.13 % as compared to DyMORA. MMOHRA outperformed SHRP and DyMORA in terms of packet Delivery Ratio (PDR) by 10.17 % and 9.83 % respectively.

For monitoring burst events in a kind of reactive wireless sensor networks (WSNs), a novel scheme of dynamic clustering routing algorithm (DCRA) based on support degree is proposed. The new approach lets sensors decide whether become a clusterhead (CH) according to the support degree coming from neighbors. Unlike traditional distributed clustering algorithms, DCRA combines energy, load balancing and topology information together by defining an objective function based on support degree. Furthermore, the clusterhead aggregates data and transmits the result to base station (sink node) along multiple paths. The new algorithm is completely distributed and location-unaware. Simulation results show that DCRA has great potential in efficiently distributing energy consumption and extending the network lifetime.

Geographic routing has been considered as an efficient, simple, and scalable routing protocol for wireless sensor networks since it exploits pure location information instead of global topology information to route data packets. Geographic routing requires the source nodes to be aware of the location of the sink nodes. How source nodes efficiently obtain the sink location information has been merely studied yet. In this paper, we propose a Sink Location Service via Inner Rectangular in Wireless Sensor Networks. A source node and a sink node send location queries and location announcement messages to specified direction respectively by geographic routing; thus, a sink location query path and a sink location announcement path is generated. The node located on a crossing point of these two paths informs the source node about the sink location information. Then the source node sends data to the sink node by geographic routing. The proposed scheme constructs a virtual restricted linear flooding zone inside the network to guarantee the existence of the crossing point. Simulation results show that proposed scheme is reliable and efficient than the existing protocols.

With development of Internet of Things, wireless sensor networks (WSN) become larger and larger and if the present clustering and routing methods are widely used in large scale WSN, “energy hole” problem will deteriorate. To alleviate “energy hole” problem of WSN, a dynamic broadcast radius-based clustering and routing algorithm (DBRCR) is proposed. The algorithm calculates node broadcast radius every round, and based on the broadcast radius the neighbor table is established. Then according to the degrees of nodes, construct clusters iteratively. Finally, finding intra-cluster communication path based on data transmission success rate and routing for the inter-cluster communication based on nodes' residual energy and transmission energy consumption to minimize the data packet-loss rate and prolong the network lifetime.

In our previous work, we elaborated the multistage virtual path (VP) control strategy and the VP topology optimization problem in which we assume a set of alternative routes exist between each source-destination (SD) pair. In the first part of this paper, a supplementary algorithm, which can yield all possible routes between two nodes and can be used for general routing problems, is provided. Based this algorithm, a dynamic VC routing policy is studied. The proposed policy distinguishes from other strategies in that it is considered in a generic networking environment. In the last part of this paper, we present a dynamic VP routing algorithm which is an important component of the dynamic VC routing policy. Detailed analyses and experimental results demonstrate these algorithms are correct, practical and useful.

The Effects of Interference on Video Quality Over Wireless Sensor Networks

Wireless Sensor Networks (WSNs) is one of the most rapidly growing research domain.This is because of the development of sensor nodes with extremely low cost and the applications of such sensor nodes are ever growing.WSNs are group of sensor nodes with a set of processors and limited memory unit.Reliable routing of packets from sensor nodes to its base station is the most important task for these networks.Also mobility of the nodes is considered to be one major criterion for WSNs.In this paper, a dynamic routing algorithm called the Mobility Assisted Dynamic Routing (MADR) algorithm has been proposed for the mobile wireless sensor networking system, where both the base station and the sensor nodes are in moving condition.The cluster head selection is based on three parameters: the energy efficiency of the sensor nodes, the mobility of the sensor nodes and the accessibility to the neighboring sensor nodes.The concept of cluster head panel is applied additionally to minimize the re-clustering time.The proposed algorithm is compared with an existing algorithm Low Energy Adaptive Clustering Hierarchy (LEACH).The simulation results show an excellent prolongation in overall network lifetime.

The capsule network is a novel architecture to encode feature attributes and spatial relationships of an image. By using the dynamic routing (DR) algorithm, a capsule network (CapsNet) model can be trained. However, the original three-layer CapsNet with the DR algorithm performs poorly on complex data sets, such as FashionMNIST, CIFAR-10, and CIFAR-100. This deficiency limits the wider application of capsule networks. In this article, we propose a deep capsule network model combined with a U-Net preprocessing module (DCN-UN). Local connection and weight-sharing strategies are adopted from convolutional neural networks to design a convolutional capsule layer in the DCN-UN model. This allows considerably reducing the number of parameters in the network model. Moreover, a greedy strategy is incorporated into the design of a mask DR (MDR) algorithm to improve the performance of network models. DCN-UN requires up to five times fewer parameters compared with the original CapsNet and other CapsNet-based models. The performance improvement achieved by the DCN-UN model with the MDR algorithm over the original CapsNet model with the DR algorithm is approximately 12% and 17% on the CIFAR-10 and CIFAR-100 data sets, respectively. The experimental results confirm that the proposed DCN-UN model allows preserving advantages of image reconstruction and equivariance mechanism in capsule networks. Moreover, an efficient initialization method is explored to enhance training stability and avoid gradient explosion.

In this paper we devise an highly-efficient load balancing algorithm, called LB-HTA, for the dynamic provisioning of connections with known duration in WDM networks. We introduce a time-dependent link-weight assignment that captures future congestion of links, leveraging the knowledge of connection durations. By means of an extensive set of simulative experiments, we compare our approach to other traditional, yet holding-time agnostic, dynamic routing algorithms. For a typical US nationwide network, LB-HTA obtains significant saving in blocking probability for practical scenarios. Moreover, we address two key-questions regarding holding-time-aware dynamic routing. Three main traffic models are considered here, namely i) dynamic traffic, ii) dynamic traffic with known durations and iii) scheduled traffic: how much the knowledge of connection durations improves the performance with respect of a holding-time- agnostic solution? Is the obtained solution close to the most effective solution provided by scheduled traffic? In order to exhaustively evaluate the performance of LB-HTA, we consider as benchmark the solution obtained under the well-known Scheduled Traffic model (TI-ST) and also under an approximated, but more effective, approach for traffic scheduling, called Time-Variant Scheduled Traffic (TV-ST). For both TI-ST and TV-ST, Integer Linear Program (ILP) formulations are proposed and results compared with dynamic routing algorithms.

The trend to implement the monitoring system with a wireless sensor network has been becoming urgent due to guaranteed flight safety and the passengers comfortability in travel. In this paper, a new dynamic routing algorithm is proposed to prolong the lifetime of the monitoring system with a distributed network based on the K‐coverage method, and filter algorithm to be used for data fusion. Finally, the simulation results validate the effectiveness of the proposed approach.

The dynamic routing algorithm for renewable wireless sensor networks with wireless power transfer

Multisource multipath data routing to a remote sink node is an effective way to cope with unreliable and malicious nodes in autonomous wireless sensor networks (WSNs). In this paper we analyze the optimal amount of redundancy in terms of the number of source sensors sensing the same physical phenomena and the number of paths through which data are routed to a remote sink node in the presence of unreliable and malicious nodes so that the query success probability is maximized while maximizing the sensor network lifetime. Our dynamic multisource multipath routing algorithm design integrates with a voting-based distributed intrusion detection algorithm to remove malicious nodes from the sensor network. By controlling the redundancy level for multisource multipath and intrusion detection settings dynamically with energy considerations as prescribed by our algorithm, we demonstrate that the lifetime of a query-based autonomous WSN is maximized in response to changing environment conditions including node density, radio range, and node capture rate.

Multimodal routing services with public transportation are already present in many large cities across the globe. In this paper we describe a mobile guide that goes beyond existing solutions, mainly due to its service personalization and its dynamic routing algorithm. Personalization is based on knowledge engineering principles and Semantic Web technologies. The dynamic routing algorithm is based on short term history and estimators and supports cities with pre-installed fleet management systems in the public transport means.

This paper considers the simulation of Wireless Sensor Networks (WSNs) using new approach. We present Sensoria, a fully fledged simulator for WSNs that has considerable differences to all other existing simulators. Sensoria is very powerful in simulating a range of small to large scale WSNs based on a simple and complete Graphical User Interface (GUI). Sensoria's GUI allows users to design various simulation scenarios and display the simulation results graphically with many formats. Sensoria is a component-based simulator and it can be easily reconfigured to adapt to different levels of simulation details and accuracy. We demonstrate the usage of Sensoria via studying many performance metrics of a set of simple and flat routing protocols that are customized by Sensoria. The paper concludes with evidence that, albeit being simple and ease-of-use, Sensoria proves to be efficient and effective tool for WSN research purposes.

Wireless Sensor Networks (WSNs) is an emerging field of engineering with various applications. They have emerged as a new class of large scale networks of embedded systems with limited communication, computation and energy resources. Recently adopted IEEE 802.15.4 standards for Low-rate Wireless Personal Area Network (LR-WPAN) are most extensively used communication platform for WSNs. Conventional routing in IEEE 802.15.4 networks is based on Ad hoc On-demand Distance Vector (AODV) which facilitates the building of mesh networks for data dissemination. The Dynamic MANET On-demand (DYMO) routing protocol is a simple and fast routing protocol which is still in its internet draft and is in its 21 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">st</sup> version. It is designed basically for multi-hop ad-hoc networks. In this paper we present a performance evaluation of DYMO routing protocols for IEEE-802.15.4 enabled WSNs. The performance of routing protocols is carried out base upon average energy consumption, average throughput, average end to end delay and average battery consumption and is compared with presently used AODV.