ENERGY CONTROLLED EVENT
REPORTING IN EVENT-DRIVEN
SENSOR NETWORKS
PUSHPA MAMORIYA
Department of Computer Applications, U.I.E.T., C.S.J.M. University, Kanpur, U. P., India
Abstract:
Wireless sensor networks (WSN) encounter spatially-correlated traffic due to high density of node deployment that is commonly found in detection and tracking applications. Due to spatial correlation among readings of nodes that are observed by a single event, it is not compulsory for every sensor node to transmit its informations to the distant sink node. This paper aims by exploiting the broadcast nature of wireless channel for conserving the energy in spatially-correlated WSN. The reporting energy of an event depends on following factors as residual energy of node, number of nodes reporting a detected event, and the frequency of occurrence of an event. The collaborate nature of event reporting using multiple nodes reduces power consumption and hence overall network life time will increase. We show that 30 % to 50 % energy saving is achieved by minimizing the redundant information in spatially-correlated WSN.
Keywords: Energy-efficient, Spatial correlation, Wireless Sensor Networks, Event reporting.
1. Introduction
The recent development of wireless sensor network (WSN) have enabled low cost, low power sensor nodes which are capable of sensing, computing and transmitting sensory data in environments such as surveillance fields, smart-homes, offices, intelligent transportation systems. Due to limited battery power, processing, and storage ability, energy-efficiency is primary objective in design of protocols for wireless sensor networks [6]. A few special sensor nodes called sink nodes collect the useful information from these sensor nodes via single-hop or multi-hop communication. The sink nodes normally are designed to be more powerful than the ordinary nodes in terms of energy, processing and storage. A large number of sensor nodes (except the sink nodes) are densely deployed inside or close to phenomenon to monitor the events of interest and send the sensory data to the sink nodes in the presence of a detected event. This paper presents a scheme for extending life-time of the network by minimizing the number of nodes in sending the reports of same event. Upon acceptance, authors are required to submit their data source file including postscript files for figures.
2. Motivations
Once an event is detected in a particular region of network, a subset of nodes inside the region are activated to generate traffic and report it to the sink. However numbers of nodes in a subset depend on range of detected event which is property of sensor hardware used to measure environment conditions such as temperature, light etc. Since one event triggers many nodes within sensing range, all the nodes have redundant information associated with single event. If the nodes can determine the correlated nodes by collaborating each other, the number of redundant information can be suppressed by reducing the number of nodes, thus the total amount of energy consumed in reporting the event is reduced. Therefore, network life-time can be increased by suppressing the redundant information in dense wireless sensor networks.
Data collection in sensor network application follows the naturally formed tree structure from many to one communication. However, data collection can happen in following ways:
A sink node can collect the data from sensor nodes periodically.
A sink node can send queries to sensor nodes as a request for data.
Based on detection of an event, sensor nodes can send reports to the sink node.
cluster, one cluster head is elected. In this way, many cluster-heads are selected and each cluster-head are assigned with one group of nodes (clusters). The function of cluster-head is to collect the data from their cluster and send it to the sink directly. To reduce number of packets sent to sink node, cluster-head use aggregation and compression mechanism to save power consumption before forwarding it to sink node. Like data aggregation and compression techniques, we are motivated with this example that number of reports can be minimized by removing correlated nodes using cluster-head. Thus power consumption can be reduced to increase the life-time of networks.
3. Related Work
Once an event is detected in the range of nodes, each node locally decides its rules based on energy available. Various protocols have been designed based on energy management and information control. These protocols are focused on increasing life-time of network with increased reliability. Some protocols are shortly summarized below:
3.1. DEALS/RMR (Information ManageD Energy Aware aLgorithm with Rule Managed Reporting) [3]:
Sub-headings In RMR, the different sets of rules according to different events occurring into sensed environment is used to balance the energy usage. These rules include threshold rules (a predefined minimum value to limit sensed value), differential rules (variation into sensed value), feature rules (based on patterns or feature observed in sensed value), periodic rules, and routine rules (rule to determine importance of a packet sent for a period of time). Once an event occurs, a node makes decision based on these rules whether event should be report or not. According to differential rules, the reports sent by nodes are assigned different priorities. IDEALS assign a power priority rule to each node based on residual available energy. Likewise, forwarding/creating of reports also depend on power priority of the each node. So a node with low residual energy will avoid forwarding a low priority event reports.
3.2. CBC (Collaborative Broadcasting and Compression) [5]:
This mechanism makes the advantage of broadcast nature of wireless channel to carry out data compression in a clustered based wireless sensor networks. The nodes deployed in the formation of clusters and cluster-heads for monitoring a geographical area. Similar to cluster-based routing mechanism, data collection is carried out from clusters to cluster-heads directly and finally, cluster-heads sent data to sink node. The idea of CBC is to allow nodes to compress their data by overhearing the neighboring nodes when clusters send data to cluster-head. Each node maintains TDMA like time slots assignment to send data to head. It is assumed that cluster-heads know residual energy and interference between clusters are negligible. Therefore, cluster-cluster-heads sub-sections and sub-subsub-sections are numbered in Arabic. Use double spacing before all section headings and single spacing after section headings. Flush left all paragraphs that follow after section headings calculate the energy by deciding which nodes have sent uncompressed data or compressed data in each round of data transmission. 3.3. DENA (Distributed Election Winner Notification Algorithm) [7]:
It is localization based distributed algorithm that identify and organize the nodes with little overhead in term of communication for an event detected into sensor field. The node closest to an event is elected as a winner node and then broadcasts its election to other nodes. The interval of time to pass this type of message is large depending on the value of derived intensity of the event. If a elected node receives a winner notification from other node before announcing its winner notification, it aborts its own election. So a node closest to the event will be elected after election round and the nodes other than elected node will cancel its own election. Finally the elected node sends data to report the event.
3.4. CAP (Corroborative Aggregation Protocol) [2]:
It is based on fusion to improve the reliability of the event reports. The event information from nodes that detect the event, are fused to increase the credibility. The nodes that perform the fusion on corrected reports while faulty reports are ignored. It overhears the reports from its neighbors when it operates in promiscuous mode. If a node overhears the report from neighboring nodes and finds dispute report, then it sends negative packet to cluster-head. The number of negative packets is used to reduce credibility of a report and hence the faulty reports are detected.
4. Problem Statement
consume more power unnecessary, one node must report the event in such a way that data received at the sink node is accurate enough. Thus, the total energy consumed in reporting an event is minimized and network life-time is increased significantly.
4.1. Main issues to be considered
Followings are the main issues or factors that need to be addressed for tacking the above problem: 1.Specific factors that decide whether to report an event or not.
2.Need to know how many nodes have detected and reported the same event. 3.How an event uniquely identified.
4.How can a sink node tune the system to fulfill the precision of data received with minimum power consumption?
5. Proposed Algorithm
In this section, we present the Energy Controlled Event Reporting (ECER) algorithm by exploiting the broadcast nature of wireless channel for event-driven wireless sensor networks.
Since wireless channel is characterized by its broadcast nature, any node can hear transmission from its neighboring node regardless of whether it is destination node or not. Therefore, this paper focuses on exploiting the broadcast nature of wireless channel into consideration and information about residual energy available at each node. In this way, a node can easily determine that any of its neighboring nodes have already reported the same event. Thus nodes can refrains itself from reporting at the same time. So that, the total number of packets reported for an event can be minimized and hence total energy consumption is reduced significantly. When an event senses by a node, it waits for a predefined period of time before reporting it. This duration depends on following factors:
How frequently the event is appeared into sensor field.
The remaining available power for a node (residual energy).
The detection range of an event (intensity of the event).
The inter-arrival time of events (identity of event) Therefore the wait time, denoted by
T
eventis calculated as follows:1 / log(
)
log(
)
event
T
Intensity of event
residual energy
. (1)Where,
and
are constant parameters. If a node overhears a report of same event within it avoid its report to send for the same event. Based on above factors, the sink node tunes the system according to weights that are control parameters to select precision of data and consumed energy for an event as application requirements. There must a inter-arrival time of the events, so a node can identify the different occurring events, for example, suppose a node, (say ‘A’) overhears a packet for an event in a given time, same event was also detected by ‘B’ in same time. The node ‘A’ then refrain its reports to send it to the sink node. If an event is detected by node ‘A’ after fixed inter-arrival time of events, then it considers it another event. Therefore, in this scheme, we use the ‘time difference’ that is the time elapsed between detecting the events, called inter-arrival time of the events. It is defined that the time elapsed between time of detecting the event and time of successful transmission of report for the same event.6. Simulation Results
The Energy Controlled Event Reporting (ECER) algorithm is simulated and performance of ECER is compared with brute force method using the J-Sim [9] network simulator. J-Sim is a component based network simulator that uses a framework for wireless sensor network applications. It consists of following components: target based traffic, sensor nodes as an entities, sensor channel and wireless communication channels and sensor network application protocols such directed diffusion, LEACH etc.
6.1. Network Architecture
6.2. Energy Model
The sink node is powerful node with unlimited energy and processing capabilities. The Mica2 motes [1] are used as sensor nodes with the properties as given in Table 1.
Table 1. Sensor Node Characteristics
Battery Capacity 2000mAH
CPU Active Current 8 mA
CPU Sleep Current 8 µA
Radio Tx Current 12 mA
Radio Rx Current 8 mA
Radio Sleep Current 2 µA
Sensor Active Current 5 mA
Sensor Sleep Current 5 µA
6.3. Results
Fig. 1 shows the energy consumed in reporting, given total 100 events. In this case, we have not included the energy spent in sensing task. Since number of nodes, that are activated to report an event, are minimized by overhearing the reports from neighboring node, the energy spent of 100 events are reduced as compared with brute force method. Likewise, energy spent is minimized for split up of energy in case of radio and CPU, as shown in Fig. 2. It is observed that ECER performs better when node density increases. However, total energy spent in reporting the given numbers of events are constant in both ECER and brute force method protocols, as shown in Fig. 3.
7. Conclusion
A new heuristic, Energy Controlled Event Reporting (ECER) algorithm is introduced by exploiting the nature of wireless channel and making the use of residual energy of nodes. Based on available residual energy, at most appropriate node is selected from a set of nodes which detected an event to send its report to the sink node. Our simulation results show that ECER algorithm performs better over brute force method with different node density. The tuning of system with α and β parameters by sink node will be effective according to application requirements. In our future work, we investigate on relationship of these parameters to tune the system.
Fig.2. Comparing ECER and Brute Force Method - Split up of Energy Spent in reporting 100 events (excluding the energy spent in sensing).
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