Int J Wireless Inf Networks (2011) 18:24–38 DOI 10.1007/s10776-010-0126-9
Adaptive Pull–Push Based Event Tracking in Wireless Sensor Actor Networks Ghalib A. Shah • Muslim Bozyigit Demet Aksoy
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Received: 28 August 2009 / Accepted: 11 November 2010 / Published online: 14 December 2010 Ó Springer Science+Business Media, LLC 2010
Abstract Wireless sensor networks have attracted significant interest for various scientific, military, and e-health applications. Recently a new class of sensor networks ‘‘sensor/actor networks’’ has been introducing new research challenges due to the unique coordination requirements among sensors and actors. In sensor/actor networks, actors are the nodes that have the capability to move in the field, equipped with powerful devices and can respond to the events of interest. With this capability, autonomous operation of the network is possible without a centralized controlling mechanism. This, however, requires the network to apply cooperative mechanism to decide when and how monitoring is done to track the event and how the event will be responded. In this regard, little work has been done in terms of co-existing Push and Pull data flows in the network. In this paper, we propose an Adaptive Pull–Push (APP) based Event Tracking approach that allows sensor-to-actor communication as well as actors coordination in response to the events occurred. APP proposes two models of sensors organization: region-based organization (RAPP) and neighbor-based organization (NAPP) to alert nodes in the vicinity of reported event. APP exploits the mobility of actor G. A. Shah (&) Center for Advanced Research in Engineering, Islamabad, Pakistan e-mail:
[email protected] M. Bozyigit Department of Computer Engineering, Middle East Technical University, Ankara, Turkey e-mail:
[email protected] D. Aksoy Department of Computer Science, University of California, Davis, CA, USA e-mail:
[email protected]
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nodes to form dynamic responsibility clusters, thus ensuring an event specific response to emergencies. Routing in APP is based on Routing by Adaptive Targeting (RAT), which is a delay-constrained geographical routing protocol. Simulation results reveal significant performance improvement in terms of response time and energy conservation. Keywords Adaptive pull–push Routing with adaptive targeting Sensor-actor coordination Heterogeneous WSAN
1 Introduction Recent advances in wireless technology and the development of small, low-cost, low-energy devices has enabled deployment of large scale highly distributed and intelligent sensor networks. Increasing onboard processing capability of individual sensors allow to perform complex tasks in order to meet the network and application requirements. Such capability allows scientists and engineers to deploy autonomous and untethered networks. Various scientific and engineering applications may utilize such intelligent sensor networks in reconnaissance, surveillance, environmental and habitat monitoring, and wildlife tracking [1]. In practice, it is not only important to monitor the environment, but also to react to it. Wireless sensor and actor networks (WSANs) have been proposed for this purpose [1]. They consist of sensor nodes that observe the environment and actor nodes that react to changes in the environment, such as autonomous mobile robots, light switches or climate regulators. In WSANs, unlike sensor nodes that have resource constraints, actors are mobile and resourceful, i.e., they have higher battery power, more processing and storage
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capabilities and can communicate using long range transmission. Hence, actors can take an active role in the network towards autonomous operation without coordinating with the sink node. The main goal of traditional sensor networks has been to communicate collected data to a stationary sink node [1]. In WSANs, event data can be either sent to a sink or directly to an actor node that has the responsibility and also the capability to respond to events of interest. Sensor/actor networks are proposed to play a major role in detecting and characterizing Chemical, Biological, Radiological, Nuclear, and Explosive (CBRNE) material and other emergency cases to prevent disastrous conditions. Obviously, an immediate action is imperative to encounter the threats in such applications. For applications that require time critical actions, such as monitoring a strategic area, it is, therefore, more efficient to report the abnormal event readings directly to the nearby actors that have the responsibility to take action. Otherwise, when emergencies are reported to a stationary sink node as in traditional WSNs, after the delivery is complete the sink node still needs to communicate with the actor node in the area to take action. Intuitively, this would increase the response time. Hence, we assume that the event is reported directly to the actors rather than a stationary sink node. There are two ways to communicate the event data; Push-based delivery and Pull-based delivery [14]. In the Push policy, sensor nodes send the sensing information to the sink without receiving explicit request, which requires continuous monitoring. In contrast, with Pull based approach, events are reported in response to explicit requests received from the sink/actor. In practice, it is unnecessary to report an event data which is not of interest to the sink or the actors. Therefore Pull can help regulating the rate at which observations are made. Although this approach saves energy, it introduces higher latency in fetching event data [3]. There have been a number of studies on Push-based dissemination in WSN [20, 21, 22, 27] as well as Pull based [28]. Some hybrid Push–Pull techniques [29, 30] are also presented to overcome the drawbacks of pure Push and pure Pull based approaches. A number of coordination protocols for WSANs have also been proposed [5, 6, 7, 8, 10, 11]. Yet a substantial work needs to be done to provide a unified solution for addressing event tracking and targeting in WSANs. In this paper, we propose an Adaptive Pull–Push (APP) approach aimed to allow energy efficient sensor-actor coordination in response to emergencies. Routing in APP is based on Routing by Adaptive Targeting (RAT) protocol [2]. RAT relays the packets to dynamically relocated actors such that delay constraints can be met while energy consumption of forwarding nodes is balanced. The
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coordination in APP is organized by actors in two ways; Neighborhood-based APP (NAPP), and Region-based APP (RAPP). NAPP limits the monitoring to the neighborhood of the first event reporting node, while RAPP extends the monitoring to a larger area. APP exploits the mobility of actor nodes to form dynamic responsibility clusters to collectively achieve the goal of the application. A responsibility cluster in the field consists of a group of sensors and at least one actor. To maintain such responsibility clusters in the field, the actor position may need to be adjusted to keep them close to emergency areas and reduce the response time. Hence, APP enables relocating the actor nodes in response to received event reports. Simulation results suggest significant performance improvement in terms of response time and energy conservation. The remainder of the paper is organized as follows. Section 2 provides an overview of the existing studies in the domains of event tracking in WSNs and coordination mechanisms in WSANs. The proposed Adaptive Pull–Push protocol for actors distribution and sensor/actor organization is presented in Sect. 3. In Section 4, we describe the timing constraints in WSANs and provide an analysis to study the lower bounds of the expected latency in data routing. Performance evaluation and results are described in Sect. 5. Finally, the paper is concluded in Sect. 6.
2 Related Work Event tracking in WSANs is required for mission critical applications in which it has threefold objectives; track the event of interests in real-time, report the occurrence of event to one of the actors and perform suitable action against that event. Target tracking has been extensively studied in the context of WSNs [15, 16, 17, 18, 19]. In a simple case which is energy exhaustive, all the nodes in WSNs remain awake to detect the event and push the event report to the sink as soon as it occurs. Contrarily, sink sends the query requesting for information about the occurrence of an event [18, 19]. Nodes which detected such event reply back to the sink, where the information is held in their cache until the request arrives. Thus, the sink can obtain and track the complete event information whenever it requires. Although, this approach can significantly reduce energy consumption, it has higher delay in obtaining the information. The improvement in event tracking is made by using prediction based approach [16, 17] in which the next position of event is predicted statistically and nodes are waken up only in the predicted area. Thus, event tracking deals with detecting the event and thereafter continuously tracking its path. In [15], a cluster-based approach is investigated for target tracking protocol in WSNs. It is based on two
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algorithms; Reduced Area Reporting (RARE-Area) and Reduction of Active node Redundancy (RARE-Node) via static clustering. RARE-Area prohibits any farther node taking part in tracking. While, RARE-node reduces redundant information by identifying overlapping sensors. Thus, the approach achieves energy efficiency by activating only the nodes mandatory for tracking the target. A tree-based tracking is proposed in [19], which organizes the nodes in the form of tree rooted at the sink. Nodes detecting the objects are the leaves and intermediate nodes keep the detection information cached in order to avoid sending multiple copies of the same detected object. This protocol incurs high overhead in maintaining the tree structure. Dynamic Object Tracking (DOT) [18] is a query based object tracking protocol in which a mobile sink tracks the occurrence of an event by sending the query. Nodes that have cached the event information respond to the query and thus the mobile sink keeps chasing through such responding nodes. The approach is vulnerable to missing event information since the nodes are periodically scheduled to go in the sleep mode and do not adapt the schedule according to the tracking path. Missing the track of event occurrence would not be tolerable for the applications of WSANs. Moreover fetching event report through querying the nodes incurs much higher delay. These approaches can not be used for real-time object tracking. Thus, we need an adaptive event tracking algorithm which provides tradeoff between the energy consumption and delay in tracking event. The existing target tracking approaches can not be applied in WSANs since there are multiple destinations that requires coordination between sensors and actors for selection of a single actor and also the event data must be reported in real-time to better cope with the occurrence of events. The framework in [6] is an event-based reactive model of clustering. Cluster formation is triggered by an event so that clusters are created on-the-fly. The in-time packet delivery in terms of reliability is operated by the actor nodes. Therefore, sensor nodes react slowly to late traffic waiting for the feedback from the actors. Hence, the subject coordination framework is not suitable for timecritical events. The work assumes that the network is dense therefore it does not propose any void region prevention or recovery mechanism. Moreover, it does not implement duty cycling to save the energy of nodes. In [10], the sensor field is divided into so called maps, where each map is represented by a sensor node which detects an event the earliest. For building a map, it floods the event detection message and applies aggregation hierarchically in the map, which introduces high latency. Eventually, the approach becomes more inefficient in terms of delay and energy when the event center moves frequently that requires rebuilding maps in the field.
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Moreover, it does not support real-time routing. Delay energy-aware routing (DEAP) [11] is a greedy routing protocol proposed for WSANs that applies duty cycle for energy conservation by monitoring the queue. It switches the node to sleep mode if the queue is empty and back to active mode otherwise. There is no explicit in-time delivery model to support real-time traffic and also does not provide any actor-actor coordination mechanism. Similarly the previous approaches in [12, 13] address only the routing issues and ignore the coordination with actors for reliability of actions. Consequently, there exists no unified solution, which provides efficient configuration of sensor nodes for event tracking and targeting in WSANs.
3 Adaptive Pull–Push (APP) Based Tracking In this section, the coordination mechanism of Adaptive Pull–Push (APP) approach is presented. Here, Push corresponds to the case where sensors continuously monitor the environment to make sure that they do not miss any event. This requires nodes to be awake at all times. On the other hand, Pull instructs the sensors when to sample the environment. This helps in defining duty cycle1 of the sensor nodes. The Pull mode allows sensors to sleep at times when no monitoring is required and, therefore, allows energy conservation. However, consider a scenario where the network is deployed to observe different emergency situations that can not be predicted apriori. It is possible that an event of interest occurs prior to the wakeup time and is not observed by the sensor node. This motivates to integrate the Push and Pull to achieve the benefits of both. APP first starts in Pull mode to conserve energy. It then adopts to Push mode if an event is reported by a sensor node and hence, called as Adaptive Pull–Push mode. Besides the reporting node, some other nodes are also instructed to skip their sleep cycle to detect the possible occurrence of event; otherwise they follow their duty cycle. This aims at conserving energy like Pull but behaving like Push when necessary, i.e., when an event is detected. In APP, as actors move within a geographical delta, they report their location, event of interest, reporting interval (c) and action response capabilities including action execution delay (e) using a long-range in-network subscription message. Sensors receiving such subscription messages are expected to publish their observations of interest to the actors, resulting in a publish/subscribe relationship [31, 32]. APP is implemented in two ways: (1) Neighborhoodbased APP (NAPP), where the neighboring nodes in close vicinity of detected event are alerted, and (2) Region-based 1
The duty cycle is defined as the ratio of wakeup period to sleep period.
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APP (RAPP), where the sensor nodes in a larger region are alerted when necessary. 3.1 Neighborhood-Based APP (NAPP) In NAPP, an actor node determines the neighborhood of a node i reporting an event data and alerts the nodes in its neighborhood for possible follow up events. The neighborhood is based on the assumed event radius (
