Query-Driven Wireless Sensor Networks: History
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Contributor:
Shushant Kumar Jain
,
Rinkoo Bhatia
,
Neeraj Shrivastava
,
Sharad Salunke
,
Mohammad Farukh Hashmi
,
Neeraj Dhanraj Bokde

In the context of query-driven wireless sensor networks (WSNs), a unique scenario arises where sensor nodes are solicited by a base station, also known as a sink, based on specific areas of interest (AoIs). Upon receiving a query, designated sensor nodes are tasked with transmitting their data to the sink.

  • wireless sensor networks
  • mobile sink
  • grid-based routing

1. Introduction

Wireless sensor networks (WSNs) consist of two main components: several resource-constrained sensor nodes and a resource-rich data collector unit, called a base station or sink. Sensor nodes have sensing, computing, and communicating capabilities in order to cater to the needs of applications and provide the required sensing information to the sink [1][2][3]. Sensor nodes are strategically positioned to detect and monitor various environmental parameters, including but not limited to humidity, pressure, light levels, and more [4][5][6]. On the basis of mobility, sinks can be characterized as either static or mobile. A static sink conserves the energy of sensor nodes because it does not require them to broadcast their location periodically. However, the neighboring nodes of the static sink experience more traffic as compared to the distant nodes, and they are prone to exhausting their energy rapidly. This situation is known as the crowded center effect [7] or the energy hole problem [8]. In numerous practical scenarios, sensor nodes are deployed in challenging environments where human intervention is impractical or unfeasible [9][10]. Therefore, charging or replacing their batteries is very difficult. Mobile sink deals with this situation as it changes its location with its movement, which leads to changes in its neighboring sensor nodes. Therefore, the data traffic does not put a burden on a specific set of sensor nodes, which was the case in the static sink. Mobile sink can accumulate the data from the sensor network by following any of the three mobility patterns: random [11], fixed [12], and controlled [13][14]. The sink mobility pattern depends on application requirements and surrounding environments. However, mobility of the sink resolves the crowded center effect and extends overall network lifetime, but it requires advertisement of its location periodically, which leads to an overhead in the network. Without this information, the sensor nodes may transmit data to the outdated location of the sink, leading to a low data delivery ratio and increased latency. To alleviate the overhead associated with providing the mobile sink’s location and enhance network performance, grid-based routing protocols have been suggested. The routing protocols begin by constructing a virtual grid structure within the sensor network. Following that, a Cluster Head (CH) is chosen for every grid cell, and the remaining nodes within each cell, referred to as cell member nodes, transmit their data to their respective CHs. These CHs subsequently relay the data to the sink. This data transmission from the sensor node to the sink can be query-driven [5][15], event-driven [16], periodic [17], and hybrid. In the context of query-driven data transmission, the sink initiates the process by sending queries. Designated sensor nodes meeting the criteria specified in the query transmit the sensed data back to the sink.

2. Query-Driven Wireless Sensor Networks

Hexagonal cell-based Data Dissemination (HexDD) [18] partitions the network into six sectors using three principal lines: horizontal lines, vertical lines, and diagonal lines. Consequently, a hexagonal-shaped virtual infrastructure is created. These lines serve as designated areas for querying and data forwarding, functioning as rendezvous points. The sink initiates its query towards the central cell, which acts as the intersection point for the three primary lines. Now, the query is flooded within the lines until it encounters the requested data. Like queries, data also traverse towards the center cell and then are transmitted to the mobile sink.
Rendezvous-based Data Dissemination (RDDM) protocol [19] is a cluster-based mechanism. It first divides the sensor networks into multiple clusters and then constructs a rendezvous-based data dissemination tree by connecting all the cluster heads. The cluster head is a node that is elected from each cluster and forwards queries and data packets. One randomly moving mobile sink stays in a cluster, which is known as a rendezvous cluster head. Apart from this, all the cluster heads and sink send their query and data to the rendezvous cluster head. The selection of rendezvous cluster head is carried out according to the energy.
The Query-Driven Virtual Grid-Based Data Dissemination (QDVGDD) protocol [20] functions by partitioning the sensor field into numerous virtual grid cells. Within each cell, a specific node is designated as the Cell Header (CH). To facilitate efficient data dissemination, a mobile sink traverses along the boundary of the sensor network and transmits its query to the CH located at the boundary. Subsequently, this boundary CH forwards the query to the CH(s) within the sink’s AoI. Upon receiving the query, the sensor nodes within the network sense their environment and relay the collected data to the respective CH. These CHs then take charge of sending the accumulated data to the mobile sink.
Energy and Delay-Efficient Data Acquisition (EDEDA) [21] is also a grid-based routing protocol. It considers both base station and mobile sink. Rather than moving randomly or following a specified path, a few of the grid cells are identified, where the mobile sink sojourns for collecting the data. From each sojourning location, the mobile sink directly collects the data from nine grid cell heads. The trajectory of the mobile sink is designed in such a way that its data collection journey begins and ends at the base station, following the Hamiltonian cycle. After collecting the data, the mobile sink hands over the data to the base station in each round.
The Trajectory Planning and Route Adjustment (TARA) technique [22] adopts a grid-based approach by constructing square-shaped grid cells within the sensor network. These grid cells are evenly numbered and serve as the fundamental units of organization. A cell head is elected for each grid cell through a process that takes into account its distance from the cell’s midpoint and its remaining energy level. These cell heads are responsible for transmitting the accumulated data to the sink. To ensure effective data collection, the mobile sink follows a trajectory that traces the perimeter of the sensor field while also passing through its center. This trajectory is carefully designed to distribute the data load evenly across the network. Whenever the mobile sink pauses at a specific grid cell during its journey, all the corresponding cell heads adjust their routes towards the sink. This adjustment process adheres to a predefined set of rules, facilitating efficient data transmission and coordination.
Query-driven Ring Routing Protocol (QRRP) [23] constructs multiple, equidistant, concentric rings in the network according to the length of the network and communication range of the sensor node. When a sink stays at a particular location, it informs ring nodes. Ring nodes save this information for transmitting the data. Furthermore, the sink also sends a query to the ring node, mentioning the area of interest. The query is forwarded from the ring nodes to the sensor nodes located within the designated area. Upon sensing the data, the sensor nodes transmit it back to the ring nodes. Subsequently, the ring nodes employ angle-based routing to transmit the aggregated sensed data to the mobile sink.
The Query-driven Backbone-based Routing protocol (QBR) [24] establishes a virtual backbone within the central region of the sensor field. This backbone consists of specific nodes known as backbone nodes, some of which form connections with each other, resulting in the creation of a tree-like structure called the backbone tree. These backbone tree nodes play a crucial role in maintaining information about the sink’s location. When the sink intends to obtain data, it initiates the process by sending a query message to the closest backbone tree node. This node then forwards the query towards the requested area, extracting location information along the way. In reply to the query, the sensor nodes within the specified region transmit their sensed data to the corresponding backbone tree node. The collected data are subsequently transmitted from the backbone tree node to the mobile sink. Table 1 presents a summary of these protocols, including their structure type, sink movement type, number of sinks, and data transmission mode.
Table 1. Summary of routing protocols.
Routing Technique Structure Type Sink Movement Type Number of Sink(s) Data Transmission Mode
HexDD [18] Grid Random Multiple Query
RDDM [19] Cluster Random Multiple Query
QDVGDD [20] Grid Fixed One Query
EDEDA [21] Grid Fixed One Event
TARA [22] Grid Pre-defined One Event
QRRP [23] Ring Random One Query
QBR [24] Backbone Random One Query
VGRQ (proposed) Grid Random One Query

This entry is adapted from the peer-reviewed paper 10.3390/fi15080259

References

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