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Using Mobile Sensors to Enhance Coverage in Linear Wireless Sensor Networks

Nader Mohamed1, Jameela Al-Jaroodi2, Imad Jawhar1, and Abdulla Eid3

1The College of Information Technology, UAE University, Al Ain, UAE 2Middleware Technologies Lab., Bahrain

3The Department of Mathematics, The University of Illinois at Urbana Champaign, USA nader.m@uaeu.ac.ae ; jaljaroodi@gmail.com; ijawhar@uaeu.ac.ae; eid1@illinois.edu

Abstract – One of the main challenges of using Linear Wireless Sensor Networks (LSN) is the reliability of the connections among the nodes. Faults in a few contiguous nodes may cause the creation of holes which will result in dividing the network into multiple disconnected segments. As a result, sensor nodes that are located between holes may not be able to deliver their sensed information which negativity affects the network sensing coverage. This paper develops two models to utilize mobile sensors to help recover from these faults and enhance coverage. The first model utilizes mobile sensors to cover the holes while the second model has the feature of reallocating previously deployed mobile sensors for best possible coverage. In both models, the added mobile nodes can provide additional sensing coverage as well as enable connectivity among disconnected segments in the LSN. Evaluations and comparisons between both models are provided. In addition, an analytical model for finding the expected number of mobile sensors needed for maintaining high coverage in a LSN with specific configurations is developed and validated.

Keywords–Linear Wireless Sensor Networks, Mobile Sensors, Communication Reliability, Sensing Coverage.

I. INTRODUCTION

There are many wireless sensor networks (WSN) applications involving monitoring linear structures such as water, oil, and gas pipelines; rivers; railways; international borders; and high power transmission cables [1]. The WSN used for monitoring these infrastructure are called Linear wireless Sensor Networks (LSN). LSNs have recently received high attention from the research community. Some of the research was dedicated to develop routing protocols for LSNs [2][3], while other work was dedicated to study other issues. Some examples of these issues are analyzing the characteristics of the traffic load distribution over a randomly deployed LSN [4], developing an algorithm for an energy-balanced data gathering method for LSN [5], developing energy-efficient node replacement schemes in LSN to balance the network load and extend the network’s lifetime [6], and developing a lightweight key redistribution mechanism for LSNs [7].

One of the main challenges facing LNS is losing connectivity in the network [8][9]. This is due to faults in neighboring and consecutive nodes. Nodes can fail due to battery exhaustion, hardware failures, and natural or intentional damages. These consecutive faulty nodes form holes which may cause the LSN to be divided into multiple disconnected segments. Some of these segments will become isolated thus they cannot transfer their sensed data

to the main station. As a result the isolated segments will not provide any sensing coverage. In this paper, we propose two models to use mobile sensors to enhance the sensing coverage in LSN in case of node failures. The first model is using multiple mobile sensors that will provide sensing, filtering and relay functions in the LSN. The second model adds a reallocation strategy for the deployed mobile sensors for best possible coverage when additional failures occur. The mobile sensor nodes have the same sensing, processing, and communication capabilities and functions as the faulty nodes. Both models can provide a fast and temporary solution for the LSN to continue their sensing and communication functions until regular maintenance is due. Both models are developed, discussed, analyzed and compared in this paper. In addition, an analytical model estimate the number of mobile sensors needed to maintain high coverage for a LSN with specific configurations is developed and validated.

The proposed solutions can be used for enhancing the coverage in LSNs located in difficult areas such as under water. One example of this LSN is the one used for monitoring underwater pipelines [10]. Underwater pipelines extend for hundreds of kilometers at a depth of hundreds of meters and subjected to high pressure [11]. At such depth, it is really difficult to perform regular maintenance for the LSN. Mobile sensors can play a significant role in recovering from accidental LSN faults to maintain a good sensing coverage.

The rest of the paper is organized as follows: Section II provides background information about LSN. Section III develops and discusses the proposed models using mobile sensors to enhance the sensing coverage in LSNs and Section IV evaluates and compares the models. An analytical model for finding the expected number of needed mobile sensors for high coverage is developed in Section V. Section VI discusses the related work while Section VII concludes the paper.

II. BACKGROUND

LSNs are a special case of WSN where sensing nodes are placed along a linear structure and communication is performed in a multi-hop form in one of two linear directions (to the left or the right of the node) to the Main Control Station (MCS) that is connected to both ends of the LSN. Sensor nodes are usually initially distributed to cover the whole linear structure in terms of sensing and communication coverage. Sensors in LSN nodes can have different sensing range capabilities. In a uniform LSN where

2013 IEEE 12th International Symposium on Network Computing and Applications

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DOI 10.1109/NCA.2013.36

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n nodes with IDs from 1 to n are distributed at uniform distances, let us define the distance between two neighboring nodes i and i+1 as one distance unit. Then a LSN with healthy nodes can provide 100% sensing coverage for the monitored linear structures if the Node Sensing Rang (NSR) is one distance unit. Each node in the LSN can communicate with a few nodes on either side. The maximum number of neighboring nodes that each node can communicate with on each side is defined as the Maximum Jump Factor (MJF). As MJF increases, the LSN is more reliable as each node will have more alternatives to forward its data. Although increasing the transmission range to reach MJF nodes on each side provides better communication reliability, more energy is consumed by the nodes that usually rely on batteries for their energy needs. This will reduce the expected life of the LSN. A dynamic configuration for the wireless transmission range can provide better power management. As shown in the configuration in Figure 1, nodes 3 and 5 have failed. Therefore, the wireless range for node 4 is increased to reach nodes 2 and 6 while other nodes use a smaller transmission range to reduce the power consumption. The sensed data is transferred through the line to MCS in either direction.

Generally there is always a possibility of failure in any

network. Using an LSN increases these possibilities as sensing nodes have limited battery life and usually operate in harsh environments. When faults occur, holes in the LSN are formed. These holes are of two types. A hole (H) causes loss of sensing coverage in the failed nodes’ location however, the failed section is small enough that the functioning neighboring nodes on either side can communicate with each other, thus the network remains fully connected. However, a disconnecting hole (DH) is a larger hole where the neighboring working nodes are no longer capable of reaching each other, thus the DH will segment the network. Assume a hole Hi exists in a LSN with size Z(Hi). If Z(Hi) is smaller than MJF and NSR then sensing coverage and communication are not affected at all. However if Z(Hi) is smaller than MJF but larger than NSR, then we lose some sensing coverage. In addition if Z(Hi) is larger than both MJF and NSR, then we lose some sensing coverage and the network becomes segmented. The uncovered part of a hole U(Hi) is:

)1........()1()(

)(0)(

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�OtherwiseNSRHZ

NSRHZHU

i

ii

Using this information we can determine the percentage of coverage C achieved with the existence of holes as:

)2....(........................................)(

1

n

HUnC

k

ii�

�

��

With multiple DHs in a LSN, as shown in Figure 2, the whole area from the first DH to the last DH will be uncovered. Although, there are some healthy nodes in the middle, they will not be able to communicate with the MCS. The effect of this type of faults is similar to having a large disconnecting hole, DH1,k that expand from the first node in DH1 to the last node in DHk. Thus disconnecting holes can have significant impact on the LSN’s coverage.

III. USING MOBILE SENSORS

In this section, using mobile sensors for enhancing communication and sensing coverage in LSNs is discussed. These models help reduce the effects of failed nodes and cover the disconnected holes (DHs) such that the LSN can maintain some acceptable level of coverage until failed nodes are replaced. Each mobile sensor has sensors, processor, memory, storage, wireless transmitter and receiver in addition to mobility enabling devices. In addition, mobile sensors can be equipped with a powerful battery for movement, sensing, processing, and communication. We will discuss two models for using mobile sensor in LSNs. The first model relies on mobile sensors that will move to replace some failed nodes and remain in that position until the periodic maintenance is due. In this model, the allocated mobile sensor will stay covering the disconnected area until the faulty sensors are replaced. The second model starts as in the first with mobile sensors covering for some failed nodes. However, if more failures occur, the mobile sensor can be reallocated to different failure locations to enhance overall LSN coverage. A. Model 1 – Mobile Sensors

When multiple nodes fail, it is usually possible to create disconnecting holes DHs that will negatively affect the coverage of the LSN. A mobile sensor can be deployed and it will move linearly over the LSN to the location of the DH to provide coverage. A mobile sensor can move to a hole to provide both sensing and communication coverage as shown in Figure 3. The mobile sensor will have the same capability of a regular sensor node in the LSN. In addition, it has a GPS and a signal strength measurement device.

Figure 3. A Mobile Sensor Covers a DH. Z(DH)= 3 1 2 3 4 5 6 7 8

Figure 2. LSN with MJF=2 and with three DHs. The area from the first to the third will not be covered.

2 4 6 8 10

12

14

16

1 3 5 7 9 11

13

15

17

Z(DH1) = 2 Z(DH3)= 3 Z(DH2)= 2

1 2 3 4 5 6 7 8

Figure 1. Automatic wireless range configuration.

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Using the information gathered about the DH, the mobile sensor will position itself in the best location to cover the DH to regain coverage. The mobile sensor will provide connectivity in the disconnected segments in the LSN. In addition, it will provide sensing coverage. If MJF is 2, then one mobile sensor can cover the communication for a hole of size up to 3 nodes. Generally a mobile sensor can cover a hole with a maximum size of (2.MJF-1). If the size of a hole is larger than (2.MJF-1) than two or more mobile sensors are needed. The equation for the number of mobile sensors needed for a DH is:

)3.....(........................................)()(

����

MJFDHZm DHZ

Multiple mobile sensors can be distributed across the

LSN to provide recovery from any DH. Each mobile sensor registers itself with the closest fixed sensor nodes using a four-way handshake. For a mobile sensor to registers itself it broadcasts a registration-interest message to the closest sensor nodes. All nodes that receive the registration-interest reply with request-received acknowledgment messages that contain their ID. The mobile sensor replies to the first request-received acknowledgment sender with a registration-request message. That node then sends a registration-confirmation message to the mobile sensor. A mobile sensor is initially registered as idle (not performing sensing or communication tasks). After a mobile sensor is deployed to replace a faulty node it becomes a deployed mobile sensor.

When a fixed sensor node or deployed mobile sensor discovers a new DH it will communicate a fault-report to the closest idle mobile sensor using multiple-hop communication. Each sensor node on the fault-report path will check if it has a registered idle mobile sensor. If not, it will forward the fault-report to the next node; however, if it has a registered idle mobile sensor, it will send the request to the registered idle mobile sensor. The idle mobile sensor responds with an acknowledgment of the fault-report and starts to move to the fault location. The node then de-registers the idle mobile sensor. The mobile sensor will move to the direction of the node that reports the fault and it should adjust itself to cover the hole. Thus it will place itself in the center of the hole and establish communication with the nodes on either side of the hole. If the hole is larger and cannot be covered by one mobile sensor, the mobile sensor will place itself next to the node that reported the fault, thus reducing the size of the DH but not completely covering it. Then the deployed mobile sensor will send another fault-report through the LSN to request another mobile sensor to help cover the hole. The process may need to be repeated several times depending on the size of the hole until the hole is completely covered. Generally, two fault reports will be generated if a DH occurs as two sensor nodes on either side of the hole will initiate a fault-report in a different direction. If only one mobile sensor is needed to cover the hole, then the first to arrive and establish the connection will send a message to the second mobile sensor to stop. If more are needed, the hole will start being filled up from both sides until the hole is covered. Eventually a

mobile sensor will be able to close the hole and that one will inform the remaining mobile sensors to stop. The size of the DH and any additional information about the fault will then be relayed to the MCS to report the problem and schedule a maintenance task for the LSN.

If there is a DH as shown in Figure 3, both nodes 4 and 8 will report a fault using multiple-hop communication in opposite directions. This will lead to having two mobile sensors move to the hole. Here the DH is covered by one mobile sensor, thus the first one that arrives to the hole will cover the area. The other one will be asked to stop. In this case, it will re-register itself to the closet node. Although an idle mobile sensor has moved, this movement is good to allow an idle mobile sensor to adjust its location and be in an area where there are no other close idle mobile sensors. This way a mobile sensor can get to any other holes faster, on average. In case the hole needs more mobile sensors then both will try to cover the hole or call for more help. In such case, they may send more fault-reports.

B. Model 2 – Mobile Sensors with Reallocation Strategy

As mobile sensors have the advantage of mobility, they can be reallocated from time to time to different DHs as new DHs occur to obtain better sensing coverage. To understand the importance of mobile sensor reallocations assume the current status of the LSN used for monitoring shown in Figure 4. MJF is 2 while there are only two mobile sensors used to enhance the coverage. These two mobile sensors are already used to cover two existing DHs as shown in Figure 4. Due to using these two mobile sensors, the whole area is covered. Now assume that after some time, two more DHs occurred in the LSN as shown in Figure 5. After this situation, there are four DHs: DH1, DH2, DH3, and DH4 with ranges [2:3], [7:8], [10:11], and [14:15] respectively. These extra DHs will reduce the coverage significantly as only nodes 1, 16, and 17 will be able to operate and communicate with the main station. All other nodes from node 2 thru 15 will not be able to report any observations.

To utilize the deployed mobile sensors to enhance the coverage, the two mobile sensors are reallocated to cover DH1 and DH4 instead of DH2 and DH3 As shown in Figure 5. In this reallocation step, coverage will be significantly enhanced. In this reallocation, only 5 nodes from 7 to 11 will not provide coverage. The segments from node 1 thru 6 and from node 12 thru 17 are covered as both ends of the network are connected to the MCS.

Figure 4. LSN with MJF=2 and two DHs. 2 4 6 8 1

0 12

14

16

1 3 5 7 9 11

13

15

17

Figure 5. Reallocation of mobile sensors for better coverage. 2 4 6 8 1

0 12

14

16

1 3 5 7 9 11

13

15

17

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Let S be the number of available mobile sensors and R the number of needed mobile sensors to cover all DHs. The best strategy to use for mobile sensor reallocation in case we need more mobile sensors than available (i.e. R > S) is to complete the coverage such that the smallest disconnected segment is left out. That is we need to find the shortest segment that needs (R - S) mobile sensors without placing any mobile sensors while placing the available mobile sensors in the remaining DHs. For example, the LSN in Figure 5 has four DHs with ranges [2:3], [7:8], [10:11], and [14:15]. We have only two mobile sensors; therefore, only two DHs can be covered while the other two DHs have to be left out. Therefore, which DHs are better to be covered? We have a number of possible allocations for both mobile sensors MS1 and MS2. However, based on the above mentioned strategy, we leave the shortest segment that needs R – S = 4 – 2 = 2 mobile sensors without any mobile sensor placements. So in the example in Figure 5, if we cover DH2 and DH3 we do not solve the problem at all as the segment from node 2 thru 15 remains uncovered. If we cover DH1 and DH3 then we leave out the segment from node 7 thru 15 uncovered (i.e. 9 nodes). If we cover DH3 and DH4 we leave out the segment from node 2 thru 8 (i.e. 7 nodes). However, if we choose to cover DH1 and DH4 we get the shortest segment (i.e. 5 nodes) from node 7 thru 11 left uncovered, which includes DH2 and DH3. These will not be covered while all other DHs (DH1 and DH4) are covered with the available mobile sensors. The main reason of not covering the shortest segment is to minimize the uncovered area thus maximizing the coverage area.

IV. EVALUATIONS

Using mobile sensors can enhance the coverage and reliability of LSN. A set of simulation experiments was conducted to evaluate the effects of using mobile sensors for enhancing the coverage in LSN. The experiments compare the coverage of LSN with and without the mobile sensors. Each LSN will be initially deployed to provide full coverage. However, after some time, some faults will occur thus reducing the coverage in the LSN. In this case the LSN needs maintenance to regain full coverage again. Mobile sensors provide a temporary solution for solving sudden faults until a periodic maintenance is conducted. The simulations were developed using Java, where experimental situations were created with 10,000-node faulty LSNs that were generated randomly to have different types of faults for each situation. The results are the averages measured from all these faulty LSNs.

The first experiment was conducted to evaluate the impact of LSN size on the sensing coverage with and without using mobile sensors where both Model1 and Model2 were used. In this experiment, each node has a 6% fault rate, NSR of 1, and a MJF of 2. When using mobile sensors, we assume we have 5 mobile sensors. The results are shown in Figures 6. The results are for LSN without any mobile sensors are shown by the LSN line, for Model1 the results are shown by the MODEL1 line, and for Model2 results are shown by the MODEL2 line. Here, the Model2

results are better due to the reallocation strategy especially for large networks.

The second experiment was conducted to study the impact of available mobile sensors on the sensing coverage using both Model1 and Model2. Here, a LSN with 1000 nodes was used and each node has a 6% fault rate, a MJF of 2, and a NSR of 2. The result is shown in Figure 7. The result shows that as the number of available mobile sensors increases, the coverage is enhanced. In addition, the result shows that the Model2 provides better coverage in all cases. This is due to the reallocation strategy.

Figure 6. Impact of network size on LSN coverage. Node Fault Rate = 6%, MJF=2, NSR=1, No. of Mobile Sensors = 5.

Figure 7. Impact of number of available mobile sensors on LSN coverage. 1000 nodes, Fault Rate = 6%, MJF=2, NSR=2.

V. ESTIMATING THE NUMBER OF NEEDED MOBILE SENSORS

For good network coverage, it is important to know the number of mobile sensors needed to cover possible DHs in the LSN. In this section, we develop an analytical model that provides a way to estimate the number of mobile sensors needed to maintain high LSN coverage. Given a LSN with n uniformly distributed nodes and a specific MJF, each node has a chance to independently fail with probability f within a certain period of time T. T can be the time to a periodic full maintenance or the time that the LSN is needed to live. To know the number of needed mobile sensors, we first need to know the expected number of holes that may occur and their sizes within the time T. Knowing the number and sizes of the holes is essential to estimate the number of mobile sensors to cover these holes. To know about the expected holes, let us first find the

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probability equation that a healthy node in the LSN has a hole directly in front of it with exactly size i. We name this equation Wf,i:

)4.....(........................................)1( 2,

iif ffW ��

Here, as f increases, the chance to have a healthy node with a hole with size i in front of it also increases. As there are n nodes in the LSN and all nodes other than the last i nodes that cannot have a hole of size i in front of them, have the same chance to have a hole in front of it, then the number of holes of size i in the LSN is:

� � )5.....(........................................, inWNH ifi � �

By replacing Wf,i with Equation 4, we have: )6..(....................).........()1( 2 inffNH i

i � �� Here, as the LSN size increases the chance to have more

holes in the LSN also increases. Now, let Ri be the number of needed mobile sensors to cover all expected holes with size i. We have:

)7..(..................................................iii mNHR �

Where mi is the number of mobile sensors needed to cover a hole with size i. We can replace mi with Equation 3:

)8..(........................................

��� �MJF

iNHR ii

For any realistic value for f, it is usually a very low probability to have holes with sizes larger than a certain number in a LSN. Therefore, we can consider that we have a variable v that represents the maximum size of possible holes. Let R be the expected number of total mobile sensors needed to cover all disconnected holes. We have:

To validate the above equations, a number of simulation

experiments were conducted covering different LSN configurations as listed in Table 1. These LSN configurations have different number of nodes (n) , node fault rate (f), maximum jump factor (MJF), and node sensing range (NSR). The table also lists the expected numbers of needed mobile sensors for all LSN configurations. These numbers are calculated using Equation 9.

Table 1. Different LSN Configurations.

Net. n f MJF NSR R LSN1 2000 5% 2 2 5 LSN2 500 12% 2 2 7 LSN3 1500 22% 3 3 13 LSN4 500 20% 2 2 17 LSN5 1000 15% 2 2 20

A set of simulation experiments were conducted for the

LSNs with the configurations listed in Table 1. They were conducted using Model1 with R mobile sensors, where R is calculated from Equation 9 and listed in Table 1. In addition, the experiments were conducted to find the impact

of using different numbers of mobile sensors on the coverage using, R-4, R-3, R-2, R-1, R, and R+1 mobile sensors. The main purpose of these experiments is to find the impact of using different number of mobile sensors on the coverage and to validate whether using calculated R mobile sensors will be enough to maintain high coverage. In other words, will using less than R mobile sensors decrease the expected coverage while using more than R mobile sensors will not increase the expected coverage significantly.

For each simulation experiment, 10,000 different faulty LSN cases were generated randomly to cover different types of faults for each situation. The average of these 10,000 cases was calculated as an expected result for each experiment. The results are shown in Figure 8. As we can see, using R mobile sensors with Model2 ensures high coverage for all selected network configurations. The expected coverage is between 97% and 98% in all cases. This is generally a good coverage range. On the other hand, the expected coverage results of using less than R mobile sensors significantly dropped as we use less mobile sensors. At the same time, using more mobile sensors, more than R, will slightly enhance the expected coverage of the LSN. These results validate the developed equations.

The coverage percentage range of 97% to 98% when using R mobile sensors, is obtained due to the existence of holes that are not disconnecting holes in the network. These holes will only slightly reduce the coverage. However, the mobile sensor will cover most of the disconnecting holes, thus the coverage will not drop significantly. The results also show that using Model2 with R mobile sensors will provide better coverage than using Model1 with the same number of mobile sensors. This is mainly due to the effective reallocation scheme used in Model2. Generally, using R mobile sensors will provide good expected coverage for the average cases; it is good to use a few more mobile sensors to ensure high coverage even with worst cases if cost is not a major issue.

Figure 8. Expected coverage under different cases.

VI. RELATED WORK

The coverage problem was one of the important issues of WSN that recently got high attention [12][13][14]. Some researchers investigated using mobile sensors to enhance coverage by developing self-deployment mechanisms or by

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v

MJFiiRR

5

developing reallocation mechanisms. Poduri and Sukhatme [15] developed a strategy that maximizes area coverage with the constraint that each of the nodes has at least k neighbors. This strategy can be used for self-deployment of mobile sensor networks. Howard et al. [16] considered the problem of deploying a mobile sensor network in an unknown environment with some obstacles. They proposed an approach where the mobile sensors can spread out such that the area ‘covered’ by the network is maximized. Wang et al. [17] investigated sensor relocation issues in mobile sensor networks. A Grid-Quorum solution to quickly locate the closest redundant sensor with low message complexity was proposed. This solution is used to relocate the redundant sensors in a timely, efficient and balanced way. Other researchers [18] proposed a probabilistic field coverage using a hybrid network of static and mobile sensors. They offered an analytical study for this hybrid network. Wang et al. [19] presented a virtual force-based sensor movement strategy to enhance coverage after an initial random placement of sensors. Sensor nodes are reallocated according to the virtual force calculation. However, all of these efforts covered randomly deployed two and three-dimensional WSN. LSNs represent a special case of WSN that has its own unique characteristics and coverage problems. None of the mentioned work studied utilizing mobile sensors to enhance the coverage in LSNs, which is important for some critical applications covering infrastructures such as pipelines, long power lines, rivers, and highways.

VII. CONCLUSION

In this paper we proposed two models to use mobile sensors for enhancing the sensing coverage in faulty LSN. The first model is using multiple mobile sensors that will replace some faulty nodes to provide sensing, and relay functions in the LSN while the second model adds a reallocation strategy for the deployed mobile sensors for best possible coverage when additional failures occur. Generally, both models provide an effective temporary solution for enhancing the coverage until a regular maintenance is conducted on the LSN. This makes the proposed models suitable for critical applications located in difficult areas or terrains that cannot be easily reached such as underwater pipelines that extend for hundreds of kilometers at depths that could exceed hundreds of meters. In addition, we developed an analytical model that estimates the number of mobile sensors needed for maintaining high coverage.

ACKNOWLEDGMENT

This work is supported in part by UAEU Research grant number 3IT008.

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