Nano-CF: a Coordination Framework for macro-programming in wireless sensor networks

Wireless Sensor Networks (WSN) are being used for a number of applications involving infrastructure monitoring, building energy monitoring and industrial sensing. The difficulty of programming individual sensor nodes and the associated overhead have encouraged researchers to design macro-programming systems which can help program the network as a whole or as a combination of subnets. Most of the current macro-programming schemes do not support multiple users seamlessly deploying diverse applications on the same shared sensor network. As WSNs are becoming more common, it is important to provide such support, since it enables higher-level optimizations such as code reuse, energy savings, and traffic reduction. In this paper, we propose a macro-programming framework called Nano-CF, which, in addition to supporting in-network programming, allows multiple applications written by different programmers to be executed simultaneously on a sensor networking infrastructure. This framework enables the use of a common sensing infrastructure for a number of applications without the users having to worrying about the applications already deployed on the network. The framework also supports timing constraints and resource reservations using the Nano-RK operating system. Nano- CF is efficient at improving WSN performance by (a) combining multiple user programs, (b) aggregating packets for data delivery, and (c) satisfying timing and energy specifications using Rate- Harmonized Scheduling. Using representative applications, we demonstrate that Nano-CF achieves 90% reduction in Source Lines-of-Code (SLoC) and 50% energy savings from aggregated data delivery.

Bandwidth allocation in hexagonal wireless sensor networks for real-time communications

We present an algorithm for bandwidth allocation for delay-sensitive traffic in multi-hop wireless sensor networks. Our solution considers both periodic as well as aperiodic real-time traffic in an unified manner. We also present a distributed MAC protocol that conforms to the bandwidth allocation and thus satisfies the latency requirements of realtime traffic. Additionally, the protocol provides best-effort service to non real-time traffic. We derive the utilization bounds of our MAC protocol.

A time division beacon scheduling mechanism for IEEE 802.15.4/Zigbee cluster-tree wireless sensor networks

While the IEEE 802.15.4/Zigbee protocol stack is being considered as a promising technology for low-cost low-power Wireless Sensor Networks (WSNs), several issues in the standard specifications are still open. One of those ambiguous issues is how to build a synchronized multi-hop cluster-tree network, which is quite suitable for ensuring QoS support in WSNs. In fact, the current IEEE 802.15.4/Zigbee specifications restrict the synchronization in the beacon-enabled mode (by the generation of periodic beacon frames) to star-based networks, while it supports multi-hop networking using the peer-to-peer mesh topology, but with no synchronization. Even though both specifications mention the possible use of cluster-tree topologies, which combine multihop and synchronization features, the description on how to effectively construct such a network topology is missing. This paper tackles this problem, unveils the ambiguities regarding the use of the cluster-tree topology and proposes a synchronization mechanism based on Time Division Beacon Scheduling to construct cluster-tree WSNs. We also propose a methodology for an efficient duty cycle management in each router (cluster-head) of a cluster-tree WSN that ensures the fairest use of bandwidth resources. The feasibility of the proposal is clearly demonstrated through an experimental test bed based on our own implementation of the IEEE 802.15.4/Zigbee protocol.

An adaptive cluster based routing scheme for mobile wireless sensor networks

Clustering schemes improve energy efficiency of wireless sensor networks. The inclusion of mobility as a new criterion for the cluster creation and maintenance adds new challenges for these clustering schemes. Cluster formation and cluster head selection is done on a stochastic basis for most of the algorithms. In this paper we introduce a cluster formation and routing algorithm based on a mobility factor. The proposed algorithm is compared with LEACH-M protocol based on metrics viz. number of cluster head transitions, average residual energy, number of alive nodes and number of messages lost

Evaluation of the Power Consumption of Routing Protocols for Wireless Sensor Networks

Sensor networks are one of the fastest growing areas in broad of a packet is in transit at any one time. In GBR, each node in the network can look at itsneighbors wireless ad hoc networking (? Eld. A sensor node, typically'hop count (depth) and use this to decide which node to forward contains signal-processing circuits, micro-controllers and a the packet on to. If the nodes' power level drops below a wireless transmitter/receiver antenna. Energy saving is one certain level it will increase the depth to discourage trafiE of the critical issue for sensor networks since most sensors are equipped with non-rechargeable batteries that have limitedlifetime. Routing schemes are used to transfer data collectedby sensor nodes to base stations. In the literature many routing protocols for wireless sensor networks are suggested. In this work, four routing protocols for wireless sensor networks viz Flooding, Gossiping, GBR and LEACH have been simulated using TinyOS and their power consumption is studied using PowerTOSSIM. A realization of these protocols has beencarried out using Mica2 Motes.

Evaluation of the Power Consumption of Routing Protocols for Wireless Sensor Networks

Sensor networks are one of the fastest growing areas in broad of a packet is in transit at any one time. In GBR, each node in the network can look at itsneighbors wireless ad hoc networking (? Eld. A sensor node, typically'hop count (depth) and use this to decide which node to forward contains signal-processing circuits, micro-controllers and a the packet on to. If the nodes' power level drops below a wireless transmitter/receiver antenna. Energy saving is one certain level it will increase the depth to discourage trafiE of the critical issue forfor sensor networks since most sensors are equipped with non-rechargeable batteries that have limited lifetime.

Evaluation of the Power Consumption of Routing Protocols for Wireless Sensor Networks

Sensor networks are one of the fastest growing areas in broadwireless ad hoc networking (?Eld. A sensor node, typically'contains signal-processing circuits, micro-controllers and awireless transmitter/receiver antenna. Energy saving is oneof the critical issue for sensor networks since most sensorsare equipped with non-rechargeable batteries that have limited lifetime.In thiswork, four routing protocols for wireless sensor networks vizFlooding, Gossiping, GBR and LEACH have been simulated using Tiny OS and their power consumption is studied usingcaorwreiredTOoSuStIuMs.ingAMirceaal2izMaotitoens.of these protocols has been carried out using mica 2 motes

MAC protocols and mobility management module for healthcare applications using wireless sensor networks

Using Wireless Sensor Networks (WSNs) in healthcare systems has had a lot of attention in recent years. In much of this research tasks like sensor data processing, health states decision making and emergency message sending are done by a remote server. Many patients with lots of sensor data consume a great deal of communication resources, bring a burden to the remote server and delay the decision time and notification time. A healthcare application for elderly people using WSN has been simulated in this paper. A WSN designed for the proposed healthcare application needs efficient MAC and routing protocols to provide a guarantee for the reliability of the data delivered from the patients to the medical centre. Based on these requirements, the GinMAC protocol including a mobility module has been chosen, to provide the required performance such as reliability for data delivery and energy saving. Simulation results show that this modification to GinMAC can offer the required performance for the proposed healthcare application.

A transmission power self-optimization technique for wireless sensor networks

Wireless sensor networks (WSNs) are generally used to monitor hazardous events in inaccessible areas. Thus, on one hand, it is preferable to assure the adoption of the minimum transmission power in order to extend as much as possible the WSNs lifetime. On the other hand, it is crucial to guarantee that the transmitted data is correctly received by the other nodes. Thus, trading off power optimization and reliability insurance has become one of the most important concerns when dealing with modern systems based on WSN. In this context, we present a transmission power self-optimization (TPSO) technique for WSNs. The TPSO technique consists of an algorithm able to guarantee the connectivity as well as an equally high quality of service (QoS), concentrating on the WSNs efficiency (Ef), while optimizing the transmission power necessary for data communication. Thus, the main idea behind the proposed approach is to trade off WSNs Ef against energy consumption in an environment with inherent noise. Experimental results with different types of noise and electromagnetic interference (EMI) have been explored in order to demonstrate the effectiveness of the TPSO technique.

TCP Performance Optimizations for Wireless Sensor Networks

Since the appearance of downsized and simplified TCP/IP stacks, single nodes from Wireless Sensor Networks (WSNs) have become directly accessible from the Internet with commonly used networking tools and applications (e.g., Telnet or SMTP). However, TCP has been shown to perform poorly in wireless networks, especially across multiple wireless hops. This paper examines TCP performance optimizations based on distributed caching and local retransmission strategies of intermediate nodes in a TCP connection, and proposes extended techniques to these strategies. The paper studies the impact of different radio duty-cycling MAC protocols on the end-to-end TCP performance when using the proposed TCP optimization strategies in an extensive experimental evaluation on a real-world sensor network testbed.

Calibrating Wireless Sensor Network Simulation Models with Real-World Experiments

This paper studies the energy-efficiency and service characteristics of a recently developed energy-efficient MAC protocol for wireless sensor networks in simulation and on a real sensor hardware testbed. This opportunity is seized to illustrate how simulation models can be verified by cross-comparing simulation results with real-world experiment results. The paper demonstrates that by careful calibration of simulation model parameters, the inevitable gap between simulation models and real-world conditions can be reduced. It concludes with guidelines for a methodology for model calibration and validation of sensor network simulation models.

A reliable, traffic-adaptive and energy-efficient link layer for wireless sensor networks

The paper presents a link layer stack for wireless sensor networks, which consists of the Burst-aware Energy-efficient Adaptive Medium access control (BEAM) and the Hop-to-Hop Reliability (H2HR) protocol. BEAM can operate with short beacons to announce data transmissions or include data within the beacons. Duty cycles can be adapted by a traffic prediction mechanism indicating pending packets destined for a node and by estimating its wake-up times. H2HR takes advantage of information provided by BEAM such as neighbour information and transmission information to perform per-hop congestion control. We justify the design decisions by measurements in a real-world wireless sensor network testbed and compare the performance with other link layer protocols.

Combining Wireless Sensor Networks and Machine Learning for Flash Flood Nowcasting

This paper addresses an investigation with machine learning (ML) classification techniques to assist in the problem of flash flood now casting. We have been attempting to build a Wireless Sensor Network (WSN) to collect measurements from a river located in an urban area. The machine learning classification methods were investigated with the aim of allowing flash flood now casting, which in turn allows the WSN to give alerts to the local population. We have evaluated several types of ML taking account of the different now casting stages (i.e. Number of future time steps to forecast). We have also evaluated different data representation to be used as input of the ML techniques. The results show that different data representation can lead to results significantly better for different stages of now casting.

Wireless Sensor Network based on OCDMA for closed environments

An infrared optical wireless system is presented, consisting on autonomous remote nodes communicating with a central node. The network is designed for telecommand/telemetry purposes, comprising a large number of nodes at a low data rate. Simultaneous access is granted by using CDMA techniques, and an appropriate selection of the code family can also keep power consumption to a minimum