Wireless sensor with data and Energy Packets

This paper develops a mathematical model to determine the balance of energy input and data sensing and transmission in a wireless sensing node. Since the node acquires energy through harvesting from an intermittent source, and sensing is also carried out intermittently, the node is modelled with random arrivals of both energy and data. A buffer in the node stores data packets while energy is stored in a battery acting as an energy buffer. The approach uses the “Energy Packet Network” paradigm so that both energy and data packets can be modelled as discrete quantities. We assume that for each data packet, the sensor consumes K e energy packets for node electronics including sensing, processing, and storing and K t energy packets for transmission. We model the node's energy and data flow by a two-dimensional random walk which represents the backlog of data and energy packets. We then simplify the model using companion matrices and matrix algebra techniques that allow us to obtain a closed-form solution for the stationary probability distribution for the random walk which allows us to compute important performance measures, including the energy consumed by the node, and its throughput in data packets transmitted as a function of the amount of power that it receives. The model also allows us to evaluate the effect of ambient noise and the needs for data retransmissions, including for the case where M sensors operate in proximity and create interference for each other

Reliable data delivery in low energy ad hoc sensor networks

Reliable delivery of data is a classical design goal for reliability-oriented collection routing protocols for ad hoc wireless sensor networks (WSNs). Guaranteed packet delivery performance can be ensured by careful selection of error free links, quick recovery from packet losses, and avoidance of overloaded relay sensor nodes. Due to limited resources of individual senor nodes, there is usually a trade-off between energy spending for packets transmissions and the appropriate level of reliability. Since link failures and packet losses are unavoidable, sensor networks may tolerate a certain level of reliability without significantly affecting packets delivery performance and data aggregation accuracy in favor of efficient energy consumption. However a certain degree of reliability is needed, especially when hop count increases between source sensor nodes and the base station as a single lost packet may result in loss of a large amount of aggregated data along longer hops. An effective solution is to jointly make a trade-off between energy, reliability, cost, and agility while improving packet delivery, maintaining low packet error ratio, minimizing unnecessary packets transmissions, and adaptively reducing control traffic in favor of high success reception ratios of representative data packets. Based on this approach, the proposed routing protocol can achieve moderate energy consumption and high packet delivery ratio even with high link failure rates. The proposed routing protocol was experimentally investigated on a testbed of Crossbow's TelosB motes and proven to be more robust and energy efficient than the current implementation of TinyOS2.x MultihopLQI

ENHANCE FAIR ROUTING WITH RESOURCE FLEXIBLE NODE ALLOCATION IN WIRELESS SENSOR NETWORKS

Wireless sensor network is a network composed of a large number of sensor nodes with limited radio capabilities and one or a few sinks that collect data from sensor nodes. Sensor nodes are powered by small batteries, hence, the energy consumption in operating a WSN should be as low as possible. The wireless sensor network present all sensor nodes generate an equal amount of data packets in a WSN, nodes around a sink have to relay more packets and tend to die earlier than other nodes because the energy consumption of sensor nodes is almost completely dominated by data communication rather than by sensing and processing. Hence, the whole network lifetime can be prolonged by balancing the communication load at heavily loaded nodes around a sink. This problem is called the energy hole problem and is one of the most important issues for WSNs. Existing system analysis the heterogeneity of networks and a fair cooperative routing method, to avoid unfair improvement only on certain networks and to introduce one or a few shared nodes that can use multiple channels to relay data packets

A bounded heuristic for collection-based routing in wireless sensor networks

Wireless sensor networks are used to monitor and control physical phenomena and to provide interaction between clients and the physical environment. Clients have been typically users or user applications, but next generation wireless sensor networks will also work in machine-to-machine scenarios where some nodes can be interested in some other nodes' data. These scenarios may run the risk of becoming overloaded with messaging, a pernicious fact in particular for constrained networks where both bandwidth and power supply are limited. Resource collections can be used in wireless sensor networks to improve bandwidth usage and to reduce energy consumption, reducing the overall number of notification packets and wrapping overhead, required for the delivery of sensor data. This article proposes a heuristic algorithm for the planning of both routing and collections, in wireless sensor networks. Results show that collections are always worthwhile, and that the heuristic is able to find feasible and cost effective solutions, approaching its lower bound.FCT from Portugal within the CEOT research center [UID/MULTI/00631/2013

Optimal Energy Management Policies for Energy Harvesting Sensor Nodes

We study a sensor node with an energy harvesting source. The generated energy can be stored in a buffer. The sensor node periodically senses a random field and generates a packet. These packets are stored in a queue and transmitted using the energy available at that time. We obtain energy management policies that are throughput optimal, i.e., the data queue stays stable for the largest possible data rate. Next we obtain energy management policies which minimize the mean delay in the queue.We also compare performance of several easily implementable sub-optimal energy management policies. A greedy policy is identified which, in low SNR regime, is throughput optimal and also minimizes mean delay.Comment: Submitted to the IEEE Transactions on Wireless Communications; 22 pages with 10 figure

MEMS Piezoelectric Energy Harvester Powered Wireless Sensor Module Driven by Noisy Base Excitation

Despite recent advances in MEMS vibration energy harvesting and ultra-low power wireless sensors, designing a wireless sensor system entirely powered by a single MEMS device under noisy base excitation has remained a challenge. This paper presents a wireless sensor system co-integrated with a single MEMS piezoelectric vibration energy harvester chip excited by band-limited large amplitude noisy vibration characteristic of an automotive application. The use of soft stoppers in the MEMS package enables the harvesters to operate at an excitation level of 10 g(rms). A custom thick AlN (Aluminum Nitride) piezoelectric process is employed to fabricate the MEMS harvesters with a single MEMS chip generating 179 μW rectified power under these excitation conditions. A low-power wireless sensor module and a receiver module were also designed and demonstrated in this work. Experiments show that the wireless sensor module can be powered solely by the MEMS energy harvester commencing from the cold state. Successful wireless data transmission and receival of sensor data packets are recorded under representative conditions

SDAMQ: Secure Data Aggregation for Multiple Queries in Wireless Sensor Networks

Wireless Sensor Network consists of severely energy constrained sensor nodes and are susceptible to security attacks due to broadcast communication model. It is necessary to optimize the transmission of packets to reduce the energy consumption. In addition data has to be encrypted in order to overcome the attack from the compromising nodes. We propose Secure Data Aggregation for Multiple Queries (SDAMQ) in Wireless Sensor Networks where multiple aggregate queries from the sink are authenticated and distributed to the sensor nodes. The sensor nodes respond by aggregating data belonging to multiple coexisting queries into a single packet, there by reducing the transmission cost. The intermediary nodes aggregate the encrypted data using additively homomorphic encryption. Thus authenticated query propagation combined with homomorphic encryption provide secure data aggregation at low energy consumption. Simulation results shows that SDAMQ provides better performance

Improved Energy and Latency Efficient MAC Scheme for Dense Wireless Sensor Networks

The sensor nodes in the wireless sensor networks have limited battery power, which motivates to work on energy conserved MAC schemes for better lifetime and latency efficient. Previous work carried out in energy conserved MAC schemes are limit the idle listening time, reduces overhearing (sensor node hear a packet destined for other nodes) and minimizing the used control packet size. The current existing work presented ELE-MAC (i.e. Energy Latency Efficient MAC) which adopts less control packets to preserve energy in sparsely distributed sensor nodes of the wireless sensor networks. It performs statistically the same or better latency characteristic compared to adaptive SMAC. ELE-MAC follows the adaptive listening technique, which reduce the sleep delay introduced by the periodic sleep of each node in case of a multi-hops network. The proposal in this work, extends the ELE-MAC to work efficiently with wireless sensor network comprises of high node density by combining the RTS and SYNC control packets. The extended version uses two separate frequencies for data and control packets to avoid the use of handshake mechanisms (e.g. RTS/CTS) in order to reduce energy consumption and packet delay. It enables a receiver to send a busy tone signal on th control channel and notify the neighbors about the ongoing reception of data in progress. This process avoids packet collisions and in turn improves the node lifetime and throughput. The nodes in a sensor network have their own different traffic loads according to the tasks assigned and their locations. The extension of ELE MAC adopts the different traffic loads of each node as performance metric for reducing the latency. Each sensor node calculates its utilization after the last synchronization time, and adjusts its duty cycle according to the calculated utilization, and then send new schedule to its neighbors via broadcasting

A localization-free interference and energy holes minimization routing for underwater wireless sensor networks

Interference and energy holes formation in underwater wireless sensor networks (UWSNs) threaten the reliable delivery of data packets from a source to a destination. Interference also causes inefficient utilization of the limited battery power of the sensor nodes in that more power is consumed in the retransmission of the lost packets. Energy holes are dead nodes close to the surface of water, and their early death interrupts data delivery even when the network has live nodes. This paper proposes a localization-free interference and energy holes minimization (LF-IEHM) routing protocol for UWSNs. The proposed algorithm overcomes interference during data packet forwarding by defining a unique packet holding time for every sensor node. The energy holes formation is mitigated by a variable transmission range of the sensor nodes. As compared to the conventional routing protocols, the proposed protocol does not require the localization information of the sensor nodes, which is cumbersome and difficult to obtain, as nodes change their positions with water currents. Simulation results show superior performance of the proposed scheme in terms of packets received at the final destination and end-to-end delay

A Survey of Routing Issues and Associated Protocols in Underwater Wireless Sensor Networks

Underwater Wireless Sensor Network is newly emerging wireless technology in which small size sensors with limited energy, limited memory and bandwidth are deployed in deep sea water and various monitoring operation like tactical surveillance, environmental monitoring and data collection are performed through these tiny sensor. Underwater Wireless Sensor Network is used for exploration of underwater resources, oceanographic data collection, flood or disaster prevention, tactical surveillance system and unmanned underwater vehicles. Sensor node consist of small memory, central processing unit and antenna. Underwater network is much different from terrestrial sensor network as radio waves cannot be used in Underwater Wireless Sensor Network. Acoustic channels are used for communication in deep sea water. Acoustic Signals carries with itself many limitation. Such as Limited bandwidth, higher end to end delay, network path loss, higher propagation delay and dynamic topology. Usually these limitation results in higher energy consumption with less number of packets delivered. The main aim now a days is to operate sensor node having smaller battery for a longer time in network. This survey has discussed the state of the art Localization based and Localization free routing protocols. Routing associated issues in the area of Underwater Wireless Sensor Network has also been discussed