16-09-2016, 09:54 AM
An Efficient Data Gathering Algorithm for Wireless
Sensor Networks with Single Mobile Sink
[attachment=71059]
Abstract. In many applications of wireless sensor networks (WSNs) where
sensors are deployed in areas accessed by laid roads, sinks can be assembled on
mobile devices like bus or handcart. Compare to WSNs with static sink(s),
wireless Sensor Networks with Mobile Sink(s) (MSSNs) are more dominant at
energy economization, delay decrease and network lifetime prolongation. In
this paper, we propose a Global Best Path (GBP) data gathering algorithm
based on wireless Sensor Networks with single Mobile Sink (GBP-MSSN). It
aims at determining the best position for the single mobile sink and further
using global sensors’ information to generate the best scheme to gather data
from specified node. Generating of best scheme is conducted by GBP algorithm
which can balance energy consumption among whole sensor networks and
further prolong the network lifetime. Simulation results show that our GBPMSSN
algorithm outperforms conventional algorithms like LEACH, GAF, etc.
Introduction
Wireless sensor networks (WSNs) are composed of large number of wireless sensor
nodes which are densely deployed either inside the phenomenon or very close to it.
Sensors are usually energy-limited and deployed randomly. WSNs have a vast
application range, including military application, environment monitoring, health-care,
smart home, etc [1]. Nowadays, many communications protocols or algorithms are
proposed such as LEACH [2], GAF [3], QAZP [4], TSA-MSSN [5] etc.
With the unceasingly thorough exploitation of nature, many regions like mountains,
forest, boondocks which are inaccessible or hard to access by vehicles become easy to
access by vehicles because of roads and other infrastructures. When some disasters
like storm, fire, or pestilence disabled daily activities of humans in some areas, the
roads and other infrastructures in these regions can be also workable. In many largescale
petrochemical industries, sensors used to gather air, water or other quality
parameters are deployed in areas around the factory, and these areas can be easy to
access by vehicles.
In these scenarios, sensor fields always changes or are monitored for just several
periods of time, thus it is not cheap or wise to build a good-sized and fixed base
station (BS), namely sink. Mobile sink can solve these problems effectively.
Furthermore, it outperforms fixed sink both in energy economization, delay decrease
and lifetime prolongation of networks [6]. In addition, we argue that these mobile
sinks can be carried by public surface transportation vehicles (e.g., cars, buses) that
repeatedly pass fixed trajectories in sensor fields [7].
In this paper, we proposed a global best path data gathering algorithm for WSNs
with single mobile sink (GBP-MSSN). Before gathering data from one node, GBPMSSN
needs to know the position set that the vehicle can arrive. For each position,
the mobile sink computes locally and gets an estimation result of weight value by
considering the global information, including nodes’ positions and residual energy.
GBP algorithm can tradeoff energy consumption and lifetime of networks by share
energy cost among multiple nodes to avoid the hotspot phenomenon.
2 Related Work
Most of existing data gathering schemes or algorithms based on WSNs with single
mobile sink are application-oriented and has their limitation or extra assumptions.
Many studies focus on movement patterns of mobile sink and their main mentality is
determining the best position for mobile sink previously based on the assumption that
the mobile sink can arrive everywhere in sensor fields [8] [9] [10]. Actually, it is not
practical in most real applications. In our proposed mechanism, we consider the sink’s
position based on its reachable position set, and this is more realistic for most
applications.
In [11], an novel architecture of MSSNs in which sensors are sparsely deployed on
both sides of roads or other routes is proposed. Based on this architecture, the authors
further propose a transmission scheduling algorithm (TSA-MSSN). However, TSAMSSN
is only applicable to sparsely and along-roads deployed WSNs. In [12],
network guided data collection (NGDC) is proposed as a novel mobility control
solution. It achieves the trade-off between delay and energy consumption. However,
this method acquiesces that any position in sensor field is accessible, and actually, it
is not practical in real applications. It also asks for mass storage to the DG nodes.
Authors in [13] propose an energy-aware routing to maximize lifetime in wireless
sensor networks with mobile sink. It achieves maximum lifetime by solving optimally
two joint problems: sojourn time at different position and energy-efficient routing.
However, it suffers the same problem as NGDC has, namely assuming that the whole
sensor field is accessible.
Authors in [14] put forward a wireless sensor network with mobile relays which
have more energy than the static sensors. The cost to build and maintain such a device
is not cheap. And this method needs some of nodes to aware of the position of the
relay in real-time, as a result, these nodes suffer extra energy consumption.
61
3 Our Proposed GBP-MSSN Algorithm
3.1 System Model
Fig.1 shows the network model where black dots stand for the random deployed
sensor nodes in the sensor field, black triangle stands for mobile sink, and gray line
stands for available trajectory of the mobile vehicle. Because GBP-MSSN algorithm
is based on query and new query may make the sink reorientation, we argue that
GBP-MSSN algorithm can be used with other hierarchical or clustering protocols.
Sensor Networks with Single Mobile Sink
[attachment=71059]
Abstract. In many applications of wireless sensor networks (WSNs) where
sensors are deployed in areas accessed by laid roads, sinks can be assembled on
mobile devices like bus or handcart. Compare to WSNs with static sink(s),
wireless Sensor Networks with Mobile Sink(s) (MSSNs) are more dominant at
energy economization, delay decrease and network lifetime prolongation. In
this paper, we propose a Global Best Path (GBP) data gathering algorithm
based on wireless Sensor Networks with single Mobile Sink (GBP-MSSN). It
aims at determining the best position for the single mobile sink and further
using global sensors’ information to generate the best scheme to gather data
from specified node. Generating of best scheme is conducted by GBP algorithm
which can balance energy consumption among whole sensor networks and
further prolong the network lifetime. Simulation results show that our GBPMSSN
algorithm outperforms conventional algorithms like LEACH, GAF, etc.
Introduction
Wireless sensor networks (WSNs) are composed of large number of wireless sensor
nodes which are densely deployed either inside the phenomenon or very close to it.
Sensors are usually energy-limited and deployed randomly. WSNs have a vast
application range, including military application, environment monitoring, health-care,
smart home, etc [1]. Nowadays, many communications protocols or algorithms are
proposed such as LEACH [2], GAF [3], QAZP [4], TSA-MSSN [5] etc.
With the unceasingly thorough exploitation of nature, many regions like mountains,
forest, boondocks which are inaccessible or hard to access by vehicles become easy to
access by vehicles because of roads and other infrastructures. When some disasters
like storm, fire, or pestilence disabled daily activities of humans in some areas, the
roads and other infrastructures in these regions can be also workable. In many largescale
petrochemical industries, sensors used to gather air, water or other quality
parameters are deployed in areas around the factory, and these areas can be easy to
access by vehicles.
In these scenarios, sensor fields always changes or are monitored for just several
periods of time, thus it is not cheap or wise to build a good-sized and fixed base
station (BS), namely sink. Mobile sink can solve these problems effectively.
Furthermore, it outperforms fixed sink both in energy economization, delay decrease
and lifetime prolongation of networks [6]. In addition, we argue that these mobile
sinks can be carried by public surface transportation vehicles (e.g., cars, buses) that
repeatedly pass fixed trajectories in sensor fields [7].
In this paper, we proposed a global best path data gathering algorithm for WSNs
with single mobile sink (GBP-MSSN). Before gathering data from one node, GBPMSSN
needs to know the position set that the vehicle can arrive. For each position,
the mobile sink computes locally and gets an estimation result of weight value by
considering the global information, including nodes’ positions and residual energy.
GBP algorithm can tradeoff energy consumption and lifetime of networks by share
energy cost among multiple nodes to avoid the hotspot phenomenon.
2 Related Work
Most of existing data gathering schemes or algorithms based on WSNs with single
mobile sink are application-oriented and has their limitation or extra assumptions.
Many studies focus on movement patterns of mobile sink and their main mentality is
determining the best position for mobile sink previously based on the assumption that
the mobile sink can arrive everywhere in sensor fields [8] [9] [10]. Actually, it is not
practical in most real applications. In our proposed mechanism, we consider the sink’s
position based on its reachable position set, and this is more realistic for most
applications.
In [11], an novel architecture of MSSNs in which sensors are sparsely deployed on
both sides of roads or other routes is proposed. Based on this architecture, the authors
further propose a transmission scheduling algorithm (TSA-MSSN). However, TSAMSSN
is only applicable to sparsely and along-roads deployed WSNs. In [12],
network guided data collection (NGDC) is proposed as a novel mobility control
solution. It achieves the trade-off between delay and energy consumption. However,
this method acquiesces that any position in sensor field is accessible, and actually, it
is not practical in real applications. It also asks for mass storage to the DG nodes.
Authors in [13] propose an energy-aware routing to maximize lifetime in wireless
sensor networks with mobile sink. It achieves maximum lifetime by solving optimally
two joint problems: sojourn time at different position and energy-efficient routing.
However, it suffers the same problem as NGDC has, namely assuming that the whole
sensor field is accessible.
Authors in [14] put forward a wireless sensor network with mobile relays which
have more energy than the static sensors. The cost to build and maintain such a device
is not cheap. And this method needs some of nodes to aware of the position of the
relay in real-time, as a result, these nodes suffer extra energy consumption.
61
3 Our Proposed GBP-MSSN Algorithm
3.1 System Model
Fig.1 shows the network model where black dots stand for the random deployed
sensor nodes in the sensor field, black triangle stands for mobile sink, and gray line
stands for available trajectory of the mobile vehicle. Because GBP-MSSN algorithm
is based on query and new query may make the sink reorientation, we argue that
GBP-MSSN algorithm can be used with other hierarchical or clustering protocols.