RRP: A Register Mechanism Routing Protocol in Wireless Sensor Networks

[[abstract]]Wireless Sensor Networks (WSNs) are event-based systems that rely on the collective effort of several micro-sensor nodes. Reliable event detection at the sink is based on collective information provided by source nodes. When data needs to be gathered from a selected set of nodes and transmit to sink in the network. However the sensor nodes often face the critical challenge among all is the constraint on limited battery energy. Therefore, how to minimize the energy consumption while maintaining an extended network lifetime becomes the most critical issue in the WSNs. We present a routing protocol in cluster-based WSNs called the Register mechanism Routing Protocol (RRP). The RRP protocol is attempted to resolve the above issue. The performance of RRP is then compared to routing protocol such as HCDD (Hierarchical Cluster-based Data Dissemination in WSNs) and TTDD (Two-tier Data Dissemination Model for Large scale WSNs). The simulation results demonstrate that RRP may reach energy savings up to 21%~50%.[[notice]]補正完畢[[incitationindex]]EI[[booktype]]紙

Design and analysis of adaptive hierarchical low-power long-range networks

A new phase of evolution of Machine-to-Machine (M2M) communication has started where vertical Internet of Things (IoT) deployments dedicated to a single application domain gradually change to multi-purpose IoT infrastructures that service different applications across multiple industries. New networking technologies are being deployed operating over sub-GHz frequency bands that enable multi-tenant connectivity over long distances and increase network capacity by enforcing low transmission rates to increase network capacity. Such networking technologies allow cloud-based platforms to be connected with large numbers of IoT devices deployed several kilometres from the edges of the network. Despite the rapid uptake of Long-power Wide-area Networks (LPWANs), it remains unclear how to organize the wireless sensor network in a scaleable and adaptive way. This paper introduces a hierarchical communication scheme that utilizes the new capabilities of Long-Range Wireless Sensor Networking technologies by combining them with broadly used 802.11.4-based low-range low-power technologies. The design of the hierarchical scheme is presented in detail along with the technical details on the implementation in real-world hardware platforms. A platform-agnostic software firmware is produced that is evaluated in real-world large-scale testbeds. The performance of the networking scheme is evaluated through a series of experimental scenarios that generate environments with varying channel quality, failing nodes, and mobile nodes. The performance is evaluated in terms of the overall time required to organize the network and setup a hierarchy, the energy consumption and the overall lifetime of the network, as well as the ability to adapt to channel failures. The experimental analysis indicate that the combination of long-range and short-range networking technologies can lead to scalable solutions that can service concurrently multiple applications

An ACO and Mobile Sink based Algorithm for Improvement of ML-MAC for Wsns using Compressive Sensing

WSN is becoming key subject of research in computational basic principle because of its great deal of applications. ACO( Ant Colony Optimization) constructs the redirecting or routing tree via a method by which, for every single circular or round, Base Station (BS) chooses the root node in addition to shows the following substitute for every node. In order to prevail over the actual constraints with the sooner work a new increased method proposed in this research work. The proposed method has the capacity to prevail over the constraints of ACO routing protocol using the principle with reactivity, mobile sink and also the compressive sensing technique. In this paper we measure the main parameters that affect the wsn that are network lifetime, packets dropped, throughput, end to end delay and remaining energy for proposed algorithm and simulation results have shown that the proposed algorithm is highly effective

SOMM: A New Service Oriented Middleware for Generic Wireless Multimedia Sensor Networks Based on Code Mobility

Although much research in the area of Wireless Multimedia Sensor Networks (WMSNs) has been done in recent years, the programming of sensor nodes is still time-consuming and tedious. It requires expertise in low-level programming, mainly because of the use of resource constrained hardware and also the low level API provided by current operating systems. The code of the resulting systems has typically no clear separation between application and system logic. This minimizes the possibility of reusing code and often leads to the necessity of major changes when the underlying platform is changed. In this paper, we present a service oriented middleware named SOMM to support application development for WMSNs. The main goal of SOMM is to enable the development of modifiable and scalable WMSN applications. A network which uses the SOMM is capable of providing multiple services to multiple clients at the same time with the specified Quality of Service (QoS). SOMM uses a virtual machine with the ability to support mobile agents. Services in SOMM are provided by mobile agents and SOMM also provides a t space on each node which agents can use to communicate with each other

Simulation study for wireless sensor networks and load sharing routing protocol to increase network life and connectivity

LSU SensorSimulator is a framework for simulating wireless sensor networks. It is a customizable and extendible simulator, which allows testing and analyzing software for wireless sensor networks. The users can subclass the framework classes and customize the behavior of various network layers. This subclassing gives a way to the developers an opportunity to analyze and investigate, phenomenological, networking, robustness and scaling issues, to explore arbitrary algorithms for distributed sensors, independent of hardware constraint. The results are compared against the simulation results for ns-2 for routing protocols Directed Diffusion and GEAR. Through the comparison of results for scalability, performance and memory utilization it is observed that LSU SensorSimulator performs much better. Buddy load sharing routing protocol is a routing protocol which can be combined with any geographically aware routing protocol to increase the network life and connectivity. The performance of Buddy load sharing algorithm for network life, and it is found that for a very negligible overhead the network life and connectivity and be improved by buddy load sharing

Sensorsimulator: simulation framework for sensor networks

Wireless sensor networks have the potential to become significant subsystems of engineering applications. Before relegating important and safety-critical tasks to such subsystems, it is necessary to understand the dynamic behavior of these subsystems in simulation environments. There is an urgent need to develop a simulation platform that is useful to explore both the networking issues and the distributed computing aspects of wireless sensor networks. Current approaches to simulating wireless sensor networks largely focus on the networking issues. These approaches use well-known network simulation tools that are often difficult to extend to explore distributed computing issues. Discrete-event simulation is a trusted platform for modeling and simulation of a variety of systems. SensorSimulator is a discreet event simulation framework for sensor networks built over OMNeT++. It is a customizable and an extensible framework for wireless sensor network simulation. This framework allows the user to debug and test software for distributed sensor networks independent of hardware constraints. The extensibility of SensorSimulator allows developers and researchers to investigate topological, phenomenological, networking, robustness and scaling issues, to explore arbitrary algorithms for distributed sensors, and to defeat those algorithms through simulated failure. The framework provides modules for various layers. Applications can be implemented by using these framework modules by sub classing the framework classes and customizing their behavior at various network layers. We validate and demonstrate the usability of these capabilities through analyzing the simulation results of Directed Diffusion and GEAR. A comparison study of performance of SensorSimulator v/s NS2 for various network densities and traffic have shown that SensorSimulator is able to achieve higher scalability and requires less time for execution