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8/3/2019 SEEPI - K VinayKumar IIT Guwahati

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SEEPI: Scalable Energy Efficient Position

Independent Node Scheduling in

Wireless Sensor Networks

S. V. Rao Chirag Makwana K. Vinay KumarDepartment of Computer Science and Engineering

Indian Institute of Technology Guwahati

Guwahati - 781039, India.

{svrao, makwana, k.vinay}@iitg.ernet.in

Abstract- Wireless sensor networks can be used to

monitor environment in remote, unattended, and hostile

environment. Nodes relay on limited power source

without recharging. Therefore, one of the mostimportant requirements of Wireless Sensor Networks

(WSN) is low power consumption. One way of achievingthis is by node scheduling. That is schedule redundant

nodes to sleep mode to conserve energy. This paper

presents Scalable Energy Efficient Position Independent

(SEEPI) node scheduling technique in WSNs. Ourdesign differs from existing approaches in the way that it

does not use position information of the node. Simulation

results on NS-2.28 shows that performance is at par with

the existing methods.

I. INTRODUCTIONRecent developments in micro electro-mechanical

systems and wireless communication have made the

deployment of small, inexpensive, and low-power sensornodes capable of cooperatively monitor physical or

environment conditions. This enables us to deploy large

scale sensor network for real-life applications such as

environmental observation, habitat monitoring, intruder

detection, and so on.

Wireless sensor network nodes rely on limited power

sources and expected to last several months to a year

without recharging as may be deployed in remote,

unattended, and hostile environments. Thus, minimizing the

energy consumption is a primary design concern of wireless

sensor network systems. One way of reducing the power

consumption is by making redundant nodes to sleep. Thus,

an efficient node scheduling scheme can improve the systemlife time by reducing energy consumption in the network.

A node scheduling scheme provides a sleep and wakeup

schedule for nodes without sacrificing network connectivity

and application dependent quality of service (QoS). The

network connectivity guarantees that there exists a path

from any sensor node to the sink/base station. In WSNs,

QoS is application specific and can be measured in different

ways. For example, in surveillance applications like intruder

detection and forest fire detection, probability of detecting

an event should be high. This requires at least one sensor

node to be active in each sub-region of network. In these

applications, percentage of the area of interest covered by

active sensors may be measured as the QoS. Ensuring bothconnectivity and coverage is a new design challenge

introduced by sensor networks which demands the

integration of multi-hop wireless communication andsensing capabilities into a single platform.

In this paper, we proposed a scalable energy efficient

position independent (SEEPI) node scheduling algorithm for

WSNs. The simulation results in NS-2.28, shows that the

SEEPI performance is better than exiting methods. Rest ofthe paper is organized as follows: next section discussesrelated work, third section discusses the proposed SEEPI

protocol, fourth section presents simulation results, and fifth

and final section concludes with pointers to futures work.

II. RELATED WORKMany distinct approaches have been proposed in the

literature for node scheduling. Some of those approaches

have viewed the problem of network connectivity and

sensing coverage independently, while others have provided

solution to both. We briefly discuss these methods in this

section. For complete survey on protocols see [1].

Span [2] is an energy efficient topology maintenanceprotocol for Mobile adhoc networks (MANET). It is a

distributed randomized algorithm that conserves the energy

by turning off the redundant nodes while preserving

connectivity. Each node takes a local decision on whether to

sleep or join the forwarding backbone, as a coordinator,

based on an estimate of how many of its neighbors will

benefit and the amount of energy available with it. Being a

protocol designed for MANET, it guarantees connectivity

but there is no consideration of sensing coverage. Several

other protocols are also proposed for assuring network

connectivity like Ascent [3]. These approaches perform

better when ratio of communication range to sensing range

(Rc/Rs) is less than or equal to 1, but as the ratio increasesthe performance degrades.

Tian et al proposed a node scheduling scheme [4], which

can reduce system overall energy consumption, therefore

increasing system life time, by turning of the redundant

sensor nodes. The coverage based off-duty rule and back-off

based node scheduling scheme guarantees that the original

sensing coverage is still maintained after turning off the

redundant sensor nodes. Each node will take a decision to

turn itself on/off only based on local neighbor information.

If the whole sensing area of a node is fully covered by the

union set of its neighbors (sponsors), then it can be turned

off without affecting system overall sensing range. Any

conflict with the neighbors will be resolved by randomback-off based scheme. To calculate sponsored coverage

authors assumed that either each node knows its location


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information or is having more than one directional antenna.

Using a location information system or directional antenna

is a very costly approach for wireless sensor networks.

LORD [5] is a localized, reactive and distributed network

coverage protocol. It conserves overall system energy by

minimizing the number of active nodes, localizing the

execution to the dying sensor(s), and minimizing the

frequency of execution by reacting only to the occurrence of

a sensing hole. It consists of two phases, the set-up phaseand the steady phase. When the network is deployed

initially, the setup phase runs, at each node, to determine its

initial state, which is ON or OFF. Once a sensor node

chooses to be ON, it runs still it dies or receives an

intimation to be turned OFF. So fairness is not assured in

this protocol. The steady phase algorithm is invoked before

a sensor si dies to find a set of replacement nodes, si.replace.

This set consisting of a minimum number of sleeping

neighbors, which can cover si. To take such a decision each

node should maintain the list of its sleeping neighbors.

Moreover, it assumed a perfect and reliable communication

layer and location information is available.

CCP [6] is an integrated coverage and connectivity

protocol (CCP), which can configure the network to therequired degree of coverage. Each node takes a local

decision to be active or not based on location information of

it and its neighbors. Location information of neighbors is

maintained in a neighbor table with the help of Hello

messages. Each node runs an eligibility algorithm to decide

to be active or not. The eligibility algorithm checks whether

all intersection points1 inside its sensing circle are covered

by some neighboring sensor or not. If so, it goes to sleep

state otherwise it announces itself as active sensor by

sending a Hellomessage to all its neighbors.In CCP, Rc > 2 Rs is a sufficient condition for coverage toimply connectivity. But for the case Rc < 2 Rs, it uses Span

[2] to provide network connectivity. The eligibility

algorithm assumes each node to know its geographical

location, which is a costlier approach.

The existing protocols, on node scheduling, treat coverage

and connectivity separately. Moreover, all the proposed

solutions are dependant on the position of the nodes.

Therefore, we need a protocol with the following

requirements: first, self configuration is mandatory becauseit is inconvenient or impossible to manually configure

sensors after they have been deployed in hostile or remote

working environments. Second, the design has to be fully

distributed and localized, because a centralized algorithmneeds global synchronization and is not scalable to large

networks. Third, the algorithm should allow as many nodesas possible to be in sleep most of the time. At the same time,

it should preserve the application defined QoS. Fourth, the

protocol should be position independent. We consider these

design issues and proposed scalable energy efficient

position independent (SEEPI) node scheduling algorithm.

III. SEEPINODE SCHEDULINGIn this section we present a scalable energy efficient

position independent (SEEPI) node scheduling in WSNs.

Our protocol makes the following design assumptions:

1 an intersection point of sensing circles of two nodes

Nodes in the network are static and data deliverymodel to the sink is event driven.

Node deployment is nondeterministic and the densityof nodes is high in every region.

All sensor nodes are homogeneous. That is, havingequal communication, computation, and sensing

capability. And node failure is possible only when it

used up all its energy. We denote the communication

range and sensing range of a node by Rc and Rs

respectively.

The SEEPI is mainly divided into three phases. Set of

nodes selected in the first two phases ensures network

connectivity. The third phase nodes helps in maintaining the

coverage.

A. Node Election for Maintaining ConnectivityA set of nodes to ensure network connectivity can be

elected either using the SPAN [2] or LECA [7]. SEEPI uses

LECA, since it selects less number of nodes compare to

SPAN, to conserve power. For the sake of completeness we

briefly discuss the LECA node selection algorithm in the

following paragraphs.Each node periodically broadcasts Hello messages that

contain the nodes status (active or not), its current active

neighbors, and its current neighbors. From these Hello

messages, each node maintains a list of neighbors and active

neighbors, and for each neighbor, a list of its neighbors and

active neighbors. Nodes in the network wake up periodicallyand collect this information by listening for a brief period

before participating in the election algorithm.

Phase1 Sensor

Fig. 1. Scenario after Phase 1

1) Phase-1 (Independent Set Construction): The first

phase is a process to select the best set of nodes that

constitute the minimal independent set for the network athand. This selection is done in a distributed manner using


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the neighbor information collected through Hello packets

during listen period. Each node decides to be a active or not

based on the following heuristics:

Nodes that have higher number of neighbors without aphase-1 sensor are given more preference. Because,

such a nodes can help a larger number of neighbors in

communication.

Nodes that have power greater than certain thresholdor higher amount of percentage of remaining power

are given more preference over others to be elected as

phase-1 sensors. This introduces the required fairness

in the protocol by ensuring proper rotation in the

selection of phase-1 sensors.

These selected phase-1 sensors go back to sleep after they

have used up a fixed percentage of their power to ensure

fairness by allowing other nodes to become phase-1 sensors.

Announcement contention occurs when multiple nodes

discover the lack of a phase-1 sensor at the same time, and

all decide to become a phase-1 sensor. It resolves with a

randomized back-off delay. That is, each node chooses a

random delay value, and delays theHello

message thatannounces the nodes volunteering as a phase-1 sensor for

that amount of time. The delay value depends on the extent

to which the node is satisfies heuristics. At the end of the

delay, the node reevaluates its eligibility based on Hello

messages recently received, and makes its announcement if

and only if the eligibility rule still holds. Fig. 1 shows a

scenario after phase-1.

Phase2 Sensor

Phase1 Sensor

Fig. 2. Scenario after Phase-2

2) Phase-2 (Connecting the Independent Set): In the

second phase, more nodes are selected to connect the phase-

1 sensors and make connected network. The node selectionis based on the following criteria:

Nodes having higher amount of percentage ofremaining energy.

Nodes having more number of phase-1 sensors in the1-hop neighborhood. This rule helps in selecting a

sensor which can connect more phase-1 nodes.

Contention, if any, is also resolved using the back off

mechanism discussed earlier.

Phase2 SensorPhase1 Sensor Phase3 Sensor

Fig. 3. Scenario after Phase-3

B. Election for Maintaining Coverage (Phase-3)First two phases of the election algorithm ensures

connective. The third phase of the algorithm ensures

coverage by electing more sensors. Moreover, it elects a

small number of sensors to avoid any large redundant

coverage.

We have to choose nodes which are going to cover largeuncovered area. An inactive node need not to be selected if

it is very close to an active node, because, such a nodes

coverage area largely overlap with the near by active node.

Another observation is, if an inactive node is far away from

the active node, no need to consider such far away active

nodes for deciding the status of inactive node, becauseintersection of the coverage area of these nodes is very less.

Experimentally, we have fixed two parameters dmin = 0.2Rs

and dmax = 1.4 Rs to classify very close and far away

neighbor respectively. We need to estimate the distance of

each 1-hop neighbor to make use ofdmin and dmax. This can

be done using received signal strength. Distance of each 1-hop neighbor is maintained in the neighbor table and sends

along the Hello messages.

Sensors which are not selected in first two phases are

participating for deciding their status using the following

heuristics.

If there is an active sensor within range dmin then nodedoes not become active. This heuristic is based on the

intuition that if such sensor will become active then itwill not help in covering much area but will increase

redundancy.


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If there is no active sensor or only one active sensorwith in the range dmax then the node is eligible to

become active in this phase. Such node uses a random

back-off delay for announcing its status as active node.

After this delay period, it will again check its

eligibility and will make an announcement if eligible.

If there is more than one active sensor with in therange dmax then it will check whether there is any pair

of nodes whose distance between them is less than or

equal to dmax. If yes then the node is not eligible. This

is because if such node will become active then it will

not help in covering much area but increase

redundancy.

Nodes, which are not selected in these three phases, are

go to sleep to conserve energy. After spending a fixed

amount of time in the sleep state, each node comes up and

participates in the election process, by checking eligibilitycriteria of three phases discussed above.

C. Node WithdrawalIn order to rotate the node active status among all nodes

fairly, each node will withdraw after some fixed interval oftime or when it has used up some percentage of its energy.

Each node marks itself as a tentatively active and announces

its withdrawal by sending Hello message. A tentatively

active node still forwards packets and sense the

environment. However, the election algorithm described

above treats a tentatively active node as a non-active. A

node stays tentatively active for some fixed amount of time,

and then goes to sleep mode.

IV. SIMULATION ENVIRONMENT AND RESULTSWe simulated our algorithm in the NS-2.28 network

simulator with CMU wireless extension and compared with

CCP. The CCP code for NS-2.1b1 is obtained from [6] andported to NS-2.28. We have used the following simulation

scenario.

Fig.4. Number of active nodes VsRc/Rs

Both the protocols were run on top of the 802.11 MAC

layer in 400 X 400 m2 coverage region with 160 randomly

distributed stationary nodes. Two sources and two sinks are

placed in opposite sides one at each corner. Each of the

sources sends a CBR flow to sink node located on the other

side of the region. Each CBR flow sends 128 byte packets

with 3Kbps rate. We have used AODV routing because it

suits the event driven application environment where each

node upon detecting an event sends data to sink node and

route is established on the fly. Nodes in our simulation use

radio with a 2Mbps bandwidth and a sensing range of 50m.

We used TwoRayGround radio propagation model in all

NS-2 simulations.

Fig. 5. Average energy consumed per node VsRc/Rs

Fig. 6. Coverage VsRc/Rs

To measure the performance of both CCP and SEEPI

under different ratio of communication range/sensing range,

we varied the communication range by setting appropriate

value of transmission power. The results are average of five

different randomly chosen scenarios for 500 seconds.

Fig. 4, 5, 6, and 7 represent number of active nodes,

average energy consumption, coverage percentage, and

delivery ratio respectively of the protocols SEEPI and CCP

with varying ratio ofRc/Rs. The ratio of successful events

reported to sink and total events detected defined as delivery

ratio.

Fig. 4 shows that number of active nodes decreases asRc/Rs increases for both the protocols. This is because as

communication range increases the nodes required to make


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network connected decreases. Moreover, it show that our

protocol results in less number of active nodes.

As our protocol activates less number of nodes its average

energy consumption per node is less than that of CCP and

that is represented in Fig. 5. The CCP uses node location

information for activating sensors, where as SEEPI does

without it. SEEPI achieves near 100\% coverage for all

cases as shown in Fig. 6.

Fig. 7. Packet Delivery Ratio VsRc/Rs

The simulation results shows that SEEPIs performs is at

par with CPP with less power consumption and with out

using location information.

V. CONCLUSION AND FURTHER REMARKSThis paper explores the problem of energy conservation in

wireless sensor network while maintaining both connectivity

and acceptable level of sensing coverage. Our simulation

results show that the coverage and delivery ratio achieved

by SEEPI are nearer to that of CCP, while average energy

consumption of node is less than that of CCP without using

location information. Our design uses local informationstored in neighbor table, so it is efficiently scalable.

Moreover, our protocol works under node mobility also. It

would be interesting to study how SEEPT works for query

driven applications and target tracking applications.

REFERENCES

[1] Kemal Akkaya and Mohamed Younis, A survey on routing protocolsfor wireless sensor networks, Ad Hoc Networks, vol. 3, no. 3. pp.325349, 2005.

[2] B. Chen, K. Jamieson, H. Balakrishnan, and R. Morris, Span: Anenergy-efficient coordination algorithm for topology maintenance in

ad hoc wireless networks, Wirel. Netw., Vol. 8, no. 5, pp. 481494,2002.

[3] A. Cerpa and D. Estrin, ASCENT: Adaptive Self-Configuring sensor

Networks Topologies, IEEE Transactions on Mobile Computing, vol.3, no. 3, pp. 272285, 2004.

[4] D. Tian and N. Georganas, "A Coverage-preserving Node SchedulingScheme for Large Wireless Sensor Networks", 2002 [online]

citeseer.ist.psu.edu/tian02coveragepreserving.html.

[5] A. Ghosh and T. Givargis, LORD: A Localized, Reactive and

Distributed Protocol for Node Scheduling in Wireless SensorNetworks, in DATE, pp. 190-195, 2005.

[6] X. Wang, G. Xing, Y. Zhang, C. Lu, R. Pless, and C. D. Gill,Integrated coverage and connectivity configuration in wireless

sensor networks, in SenSys, pp. 2839, 2003.[7] R. Hegde, Power aware mobile ad hoc networks", M.Tech Thesis,

Indian Institute of Technology Guwahati, 2005.

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