Redundant Actor Based Multi-Hole Healing System for Mobile Sensor Networks
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In recent years, the Mobile Wireless Sensor Network is the emerging solution for monitoring of a specified region of interest. Several anomalies can occur in WSNs that impair their desired functionalities resulting in the formation of different kinds of holes, namely: coverage holes, routing holes. Our ultimate aim is to cover total area without coverage hole in wireless sensor networks. We propose a comprehensive solution, called holes detection and healing. We divided our proposed work into two phases. The first phase consists of three sub- tasks; Hole-identification, Hole-discovery and border detection. The second phase treats the Hole-healing with novel concept, hole healing area. It consists of two sub-tasks; Hole healing area determination and node relocation.
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![International Journal of Computer Applications Technology and Research
Volume 4– Issue 12, 923 - 927, 2015, ISSN: 2319–8656
www.ijcat.com 923
Redundant Actor Based Multi-Hole Healing System for Mobile
Sensor Networks
S. Himabindu
VBIT
Hyderabad
B. Brahma Reddy
VBIT
Hyderabad
Abstract
In recent years, the Mobile Wireless Sensor Network
is the emerging solution for monitoring of a specified region of
interest. Several anomalies can occur in WSNs that impair their
desired functionalities resulting in the formation of different
kinds of holes, namely: coverage holes, routing holes. Our
ultimate aim is to cover total area without coverage hole in
wireless sensor networks. We propose a comprehensive solution,
called holes detection and healing. We divided our proposed
work into two phases. The first phase consists of three sub- tasks;
Hole-identification, Hole-discovery and border detection. The
second phase treats the Hole-healing with novel concept, hole
healing area. It consists of two sub-tasks; Hole healing area
determination and node relocation.
Key words: WSN, coverage holes, routing holes, hole
healing.
1. INTRODUCTION
RECENT years have witnessed a growing interest in the
applications of wireless sensor-actor networks (WSANs). Of
particular interest are applications in remote and harsh areas in
which human intervention is risky or impractical. Examples
include space exploration, battle field surveillance, search-and-
research, and coastal and border protection. A WSAN consists of
a set of miniaturized low-cost sensors that are spread in an area of
interest to measure ambient conditions in the vicinity.
Given the collaborative actors’ operation, a strongly
connected inter-actor network topology would be required at all
times. Actors usually coordinate their motion so that they stay
reachable to each other. However, a failure of an actor may cause
the network to partition into disjoint blocks and would thus violate
such a connectivity requirement.
2. RELATED WORK
The [1] wireless communications systems in the mobile
computers support a broadcast mechanism, much more flexible
and useful ways of sharing information can be imagined. Our
proposed routing method allows a collection of mobile computers,
which may not be close to any base station and can exchange data
along changing and arbitrary paths of interconnection, to afford all
computers among their number a (possibly multi-hop) path along
which data can be exchanged. In addition, our solution must
remain compatible with operation in cases where a base station is
available. By the methods outlined in this paper not only will
routing be seen to solve the problems associated with ad-hoc
networks, but in addition authors will describe ways to perform
such routing functions at Layer 2, which traditionally has not been
utilized as a protocol level for routing. Packets are transmitted
between the stations of the network by using routing tables which
are stored at each station of the network. Each routing table, at
each of the stations, lists all available destinations, and the number
of hops to each. Each route table entry is tagged with a sequence
number which is originated by the destination station. To maintain
the consistency of routing tables in a dynamically varying
topology, each station periodically transmits updates, and
transmits updates immediately when significant new information
is available, since authors did not assume that the mobile hosts are
maintaining any sort of time synchronization, authors also make
no assumption about the phase relationship of the update periods
between the mobile hosts. These packets indicate which stations
are accessible from each station and the number of hops necessary
to reach these accessible stations, as is often done in distance-
vector routing algorithms.
In [2] report, authors focus on the specific problem of
altering the positions of robots in order to achieve a desirable ad
hoc network topology starting from an arbitrary initial spatial
configuration. Every robot node includes its location information
(GPS coordinates or indoor relative location information)
whenever it floods an LSU (link state update) to the rest of the
network. Additionally neighbour information of a node is also
extracted from an LSU in order to construct a view of the current
network topology.](https://cdn.statically.io/img/image.slidesharecdn.com/ijcatr04121008-160119101315/85/Redundant-Actor-Based-Multi-Hole-Healing-System-for-Mobile-Sensor-Networks-1-320.jpg)
![International Journal of Computer Applications Technology and Research
Volume 4– Issue 12, 923 - 927, 2015, ISSN: 2319–8656
www.ijcat.com 924
In [2] article authors show that iterative block
movement algorithm significantly. Authors have considered a bi-
connected network where nodes still can exchange messages with
each other to coordinate the recovery process even after failure.
And finding an exact polynomial time optimization algorithm for
the 2D case is extremely hard. [3] Paper considers the
connectivity restoration problem subject to path length
constraints. Basically, in some applications, such as combat
robotic networks and search-and-rescue operation, timely
coordination among the actors is required, and extending the
shortest path between two actors as a side effect of the recovery
process would not be acceptable.
In [4] paper, authors designed and evaluated distributed self-
deployment protocols for mobile sensors. After discovering a
coverage hole, the proposed protocols calculate the target
positions of the sensors where they should move. Author problem
statement is: given the target area, how to maximize the sensor
coverage with less time, movement distance and message
complexity. In [4] paper authors addressed the problem of placing
sensors in target field to maximize the sensing coverage. Although
the centralized approach may minimize the sensor movement,
central server architecture may not be feasible in some
applications.
2.1 Existing system & Disadvantage
In existing research works, the researchers proposed the
technique with movement assisted sensor node deployment and
then Hole-detection works by a node decides whether it is on the
boundary of a hole by comparing its degree with the average
degree of its 2-hop neighbors. Not all boundary nodes can be
identified correctly by this algorithm.
3. PROPOSED SYSTEM
Our proposed hole and border detection algorithm is distributed
and lightweight, and thus more suited to the energy constrained
WSNs. we propose collaborative mechanisms to detect and heal
holes. Our hole-detection mechanism deals with holes of various
forms and sizes. We try to alert a limited number of nodes
surrounding the hole, only those nodes have the task of moving
and repairing the hole. In this section, we are going to discuss
about our enhancement work. Our base method works like
reactive mode, if the node is failed then only Hole healing will be
start. By our base work wes can cover the holes, but reactive mode
will be cause to high level topology changes, and the more number
of nodes has to move from own position. Due continuous node
failure, the network may not be healed after certain healing
process. To avoid this type of problem, we propose the extra
temporary SensRob’s. in our Enhancement we propose the failure
detection based on the energy loss. The node will fail when it
loosed remaining energy less than critical level. So in our
enhancement, we propose the technique to detect failure of node
due to the energy loss.
Each node in the network monitors the own energy loss,
if own energy is getting reduce near to critical level then the node
will inform to the base station about energy loss. Once base station
received error message from the sensor the it will check
availability of extra actor. The base node will share the position
information of critical node and id details to the extra actor, and
then the extra actor has to move to the critical node position.
After reaching the place of critical node, the extra actor
has to inform to the critical node to inter change the id in
neighbor’s neighbor table. The critical node will send the inter
change message to neighbor with extra actor id. The neighbors of
critical node need to change their neighbor table info such as extra
actor id will be placed as the neighbor sensor and neighbor sensor
(critical node will be deleted). After id inter changing process, the
critical node will be treated as extra actor and extra actor will be
treated as normal sensor device, then the extra actor node (inter
changed critical node) has to move to base station and its need to
repair the energy level. This reclaimed extra actor can be placed
in any other critical node in future.
3.1 Algorithm
Hole detection & Healing :
1) Initialize the Htimer and Neigh_timer
2) If 𝑻𝒊𝒎𝒆𝒓 𝒆𝒙𝒑𝒊𝒓𝒆
– Generate the hello message
• 𝑃𝑘𝑡 ← 𝑛𝑑𝑖𝑑& 𝑃𝑜𝑠(𝑥, 𝑦)
– Broadcast Hello message
– 𝑆𝑐ℎ𝑒𝑑𝑢𝑙𝑒(𝑇𝑛𝑜𝑤 + 𝑇𝑅𝑎𝑛𝑑 𝑐𝑜𝑛𝑠𝑡
)
3) If 𝑷𝒌𝒕 Recv in node in 𝒏𝒊
– If 𝑃𝑘𝑡. 𝑡𝑦𝑝𝑒 = 𝐻𝑒𝑙𝑙𝑜
• Set 𝐼𝑛𝑠𝑒𝑟𝑡 = 𝑡𝑟𝑢𝑒
• Foreach 𝑴 ∈ 𝑻𝒃𝒍 𝑵](https://cdn.statically.io/img/www.slideshare.net/data:image/gif;base64,R0lGODlhAQABAIAAAAAAAP///yH5BAEAAAAALAAAAAABAAEAAAIBRAA7)
Redundant Actor Based Multi-Hole Healing System for Mobile Sensor Networks
- 1. International Journal of Computer Applications Technology and Research Volume 4– Issue 12, 923 - 927, 2015, ISSN: 2319–8656 www.ijcat.com 923 Redundant Actor Based Multi-Hole Healing System for Mobile Sensor Networks S. Himabindu VBIT Hyderabad B. Brahma Reddy VBIT Hyderabad Abstract In recent years, the Mobile Wireless Sensor Network is the emerging solution for monitoring of a specified region of interest. Several anomalies can occur in WSNs that impair their desired functionalities resulting in the formation of different kinds of holes, namely: coverage holes, routing holes. Our ultimate aim is to cover total area without coverage hole in wireless sensor networks. We propose a comprehensive solution, called holes detection and healing. We divided our proposed work into two phases. The first phase consists of three sub- tasks; Hole-identification, Hole-discovery and border detection. The second phase treats the Hole-healing with novel concept, hole healing area. It consists of two sub-tasks; Hole healing area determination and node relocation. Key words: WSN, coverage holes, routing holes, hole healing. 1. INTRODUCTION RECENT years have witnessed a growing interest in the applications of wireless sensor-actor networks (WSANs). Of particular interest are applications in remote and harsh areas in which human intervention is risky or impractical. Examples include space exploration, battle field surveillance, search-and- research, and coastal and border protection. A WSAN consists of a set of miniaturized low-cost sensors that are spread in an area of interest to measure ambient conditions in the vicinity. Given the collaborative actors’ operation, a strongly connected inter-actor network topology would be required at all times. Actors usually coordinate their motion so that they stay reachable to each other. However, a failure of an actor may cause the network to partition into disjoint blocks and would thus violate such a connectivity requirement. 2. RELATED WORK The [1] wireless communications systems in the mobile computers support a broadcast mechanism, much more flexible and useful ways of sharing information can be imagined. Our proposed routing method allows a collection of mobile computers, which may not be close to any base station and can exchange data along changing and arbitrary paths of interconnection, to afford all computers among their number a (possibly multi-hop) path along which data can be exchanged. In addition, our solution must remain compatible with operation in cases where a base station is available. By the methods outlined in this paper not only will routing be seen to solve the problems associated with ad-hoc networks, but in addition authors will describe ways to perform such routing functions at Layer 2, which traditionally has not been utilized as a protocol level for routing. Packets are transmitted between the stations of the network by using routing tables which are stored at each station of the network. Each routing table, at each of the stations, lists all available destinations, and the number of hops to each. Each route table entry is tagged with a sequence number which is originated by the destination station. To maintain the consistency of routing tables in a dynamically varying topology, each station periodically transmits updates, and transmits updates immediately when significant new information is available, since authors did not assume that the mobile hosts are maintaining any sort of time synchronization, authors also make no assumption about the phase relationship of the update periods between the mobile hosts. These packets indicate which stations are accessible from each station and the number of hops necessary to reach these accessible stations, as is often done in distance- vector routing algorithms. In [2] report, authors focus on the specific problem of altering the positions of robots in order to achieve a desirable ad hoc network topology starting from an arbitrary initial spatial configuration. Every robot node includes its location information (GPS coordinates or indoor relative location information) whenever it floods an LSU (link state update) to the rest of the network. Additionally neighbour information of a node is also extracted from an LSU in order to construct a view of the current network topology.
- 2. International Journal of Computer Applications Technology and Research Volume 4– Issue 12, 923 - 927, 2015, ISSN: 2319–8656 www.ijcat.com 924 In [2] article authors show that iterative block movement algorithm significantly. Authors have considered a bi- connected network where nodes still can exchange messages with each other to coordinate the recovery process even after failure. And finding an exact polynomial time optimization algorithm for the 2D case is extremely hard. [3] Paper considers the connectivity restoration problem subject to path length constraints. Basically, in some applications, such as combat robotic networks and search-and-rescue operation, timely coordination among the actors is required, and extending the shortest path between two actors as a side effect of the recovery process would not be acceptable. In [4] paper, authors designed and evaluated distributed self- deployment protocols for mobile sensors. After discovering a coverage hole, the proposed protocols calculate the target positions of the sensors where they should move. Author problem statement is: given the target area, how to maximize the sensor coverage with less time, movement distance and message complexity. In [4] paper authors addressed the problem of placing sensors in target field to maximize the sensing coverage. Although the centralized approach may minimize the sensor movement, central server architecture may not be feasible in some applications. 2.1 Existing system & Disadvantage In existing research works, the researchers proposed the technique with movement assisted sensor node deployment and then Hole-detection works by a node decides whether it is on the boundary of a hole by comparing its degree with the average degree of its 2-hop neighbors. Not all boundary nodes can be identified correctly by this algorithm. 3. PROPOSED SYSTEM Our proposed hole and border detection algorithm is distributed and lightweight, and thus more suited to the energy constrained WSNs. we propose collaborative mechanisms to detect and heal holes. Our hole-detection mechanism deals with holes of various forms and sizes. We try to alert a limited number of nodes surrounding the hole, only those nodes have the task of moving and repairing the hole. In this section, we are going to discuss about our enhancement work. Our base method works like reactive mode, if the node is failed then only Hole healing will be start. By our base work wes can cover the holes, but reactive mode will be cause to high level topology changes, and the more number of nodes has to move from own position. Due continuous node failure, the network may not be healed after certain healing process. To avoid this type of problem, we propose the extra temporary SensRob’s. in our Enhancement we propose the failure detection based on the energy loss. The node will fail when it loosed remaining energy less than critical level. So in our enhancement, we propose the technique to detect failure of node due to the energy loss. Each node in the network monitors the own energy loss, if own energy is getting reduce near to critical level then the node will inform to the base station about energy loss. Once base station received error message from the sensor the it will check availability of extra actor. The base node will share the position information of critical node and id details to the extra actor, and then the extra actor has to move to the critical node position. After reaching the place of critical node, the extra actor has to inform to the critical node to inter change the id in neighbor’s neighbor table. The critical node will send the inter change message to neighbor with extra actor id. The neighbors of critical node need to change their neighbor table info such as extra actor id will be placed as the neighbor sensor and neighbor sensor (critical node will be deleted). After id inter changing process, the critical node will be treated as extra actor and extra actor will be treated as normal sensor device, then the extra actor node (inter changed critical node) has to move to base station and its need to repair the energy level. This reclaimed extra actor can be placed in any other critical node in future. 3.1 Algorithm Hole detection & Healing : 1) Initialize the Htimer and Neigh_timer 2) If 𝑻𝒊𝒎𝒆𝒓 𝒆𝒙𝒑𝒊𝒓𝒆 – Generate the hello message • 𝑃𝑘𝑡 ← 𝑛𝑑𝑖𝑑& 𝑃𝑜𝑠(𝑥, 𝑦) – Broadcast Hello message – 𝑆𝑐ℎ𝑒𝑑𝑢𝑙𝑒(𝑇𝑛𝑜𝑤 + 𝑇𝑅𝑎𝑛𝑑 𝑐𝑜𝑛𝑠𝑡 ) 3) If 𝑷𝒌𝒕 Recv in node in 𝒏𝒊 – If 𝑃𝑘𝑡. 𝑡𝑦𝑝𝑒 = 𝐻𝑒𝑙𝑙𝑜 • Set 𝐼𝑛𝑠𝑒𝑟𝑡 = 𝑡𝑟𝑢𝑒 • Foreach 𝑴 ∈ 𝑻𝒃𝒍 𝑵
- 3. International Journal of Computer Applications Technology and Research Volume 4– Issue 12, 923 - 927, 2015, ISSN: 2319–8656 www.ijcat.com 925 – If 𝑃𝑘𝑡. 𝑠𝑟𝑐 = 𝑀. 𝐼𝑑 𝑀. 𝑇𝑒𝑥 = 𝑇𝑛𝑜𝑤 + 𝑇𝑐𝑜𝑛𝑠𝑡 𝑀. 𝑃𝑜𝑠(𝑃𝑘𝑡. 𝑥, 𝑃𝑘𝑡. 𝑦) Set 𝐼𝑛𝑠𝑒𝑟𝑡 = 𝑓𝑎𝑙𝑠𝑒 𝑆𝑒𝑎𝑟𝑐ℎ 𝑠𝑡𝑜𝑝 • If 𝐼𝑛𝑠𝑒𝑟𝑡 = 𝑇𝑟𝑢𝑒 – Allocate new Memory 𝑀 → 𝑇𝑏𝑙 𝑁 𝑀. 𝐼𝑑 = 𝑃𝑘𝑡. 𝑠𝑟𝑐 𝑀. 𝑃𝑜𝑠(𝑃𝑘𝑡. 𝑥, 𝑃𝑘𝑡. 𝑦) 𝑀. 𝑇𝑒𝑥 = 𝑇𝑛𝑜𝑤 + 𝑇𝑐𝑜𝑛𝑠𝑡 – Else-If 𝑃𝑘𝑡. 𝑡𝑦𝑝𝑒 = 𝐻𝑜𝑙𝑒 𝑑𝑖𝑠𝑐 • If 𝑃𝑘𝑡. 𝑓𝑖𝑑 ∈ 𝑁𝑏𝑙𝑖𝑠𝑡 ∈ 𝑁𝑏𝑡𝑎𝑏𝑙𝑒 & 𝑛𝑖 ∉ 𝑃𝑘𝑡. 𝑝𝑎𝑡ℎ & 𝑃𝑘𝑡. 𝑠𝑟𝑐 ≠ 𝑛𝑖 – Set 𝑑𝑠𝑡 = 𝐷𝑖𝑠𝑡(𝑃𝑘𝑡. 𝑆𝑃𝑜𝑠 𝑥,𝑦 & 𝑛𝑖(𝑥,𝑦) ) – If 𝑑𝑠𝑡 > 𝑃𝑘𝑡. 𝑑𝑠𝑡 𝑚𝑥 𝑃𝑘𝑡. 𝑑𝑠𝑡 𝑚𝑥 = 𝑑𝑠𝑡 𝑃𝑘𝑡. 𝐶𝑝𝑜𝑠 ← (𝑥 𝑛𝑖 , 𝑦 𝑛𝑖 ) – 𝑛𝑖 ∪ 𝑝𝑘𝑡. 𝑝𝑎𝑡ℎ – 𝑅𝑒𝑠𝑒𝑡(𝑇𝑖𝑚𝑒𝑟 𝐻𝑜𝑙𝑒 𝑑𝑖𝑠𝑐 ) – Set 𝑃𝑘𝑡. ℎ𝑜𝑝 = 0 – 𝑅𝑒𝑏𝑟𝑜𝑎𝑑𝑐𝑎𝑠𝑡(𝑃𝑘𝑡) • Else-If 𝑃𝑘𝑡. 𝑓𝑖𝑑 ≠ 𝐼𝑑𝑓𝑎𝑖𝑙 & 𝑛𝑖 ∉ 𝑃𝑘𝑡. 𝑝𝑎𝑡ℎ & 𝑃𝑘𝑡. 𝑠𝑟𝑐 ≠ 𝑛𝑖 & 𝑃𝑘𝑡. ℎ𝑜𝑝 < 1 – 𝑃𝑘𝑡. ℎ𝑜𝑝 + + – 𝑅𝑒𝑏𝑟𝑜𝑎𝑑𝑐𝑎𝑠𝑡(𝑃𝑘𝑡) • Else-If 𝑃𝑘𝑡. 𝑠𝑟𝑐 = 𝑛𝑖 – If 𝑀𝐷𝑖𝑠𝑡𝑓𝑎𝑖𝑙 < 𝑃𝑘𝑡. 𝑑𝑠𝑡 𝑚𝑥 Set 𝑁. 𝑡𝑦𝑝𝑒 = 𝐻𝑀 𝑀𝐷𝑖𝑠𝑡𝑓𝑎𝑖𝑙 = 𝑃𝑘𝑡. 𝑑𝑠𝑡 𝑚𝑥 𝑥 𝑐 = (𝑥 𝑛𝑖 + 𝑃𝑘𝑡. 𝐶𝑝𝑜𝑠 𝑥)/2 𝑦𝑐 = (𝑦 𝑛𝑖 + 𝑃𝑘𝑡. 𝐶𝑝𝑜𝑠 𝑦)/2 – 𝐹𝑟𝑒𝑒(𝑝𝑘𝑡) – 𝑇𝑖𝑚𝑒𝑟 𝐻𝑜𝑙𝑒 𝐻𝑒𝑎𝑙 . 𝑆𝑐ℎ𝑒𝑑𝑢𝑙𝑒(𝑇𝑛𝑜𝑤 + 𝑇𝑅𝑎𝑛𝑑 𝑐𝑜𝑛𝑠𝑡 ) • Else – 𝐹𝑟𝑒𝑒(𝑝𝑘𝑡) – Else-if 𝑃𝑘𝑡. 𝑡𝑦𝑝𝑒 = 𝐻𝑜𝑙𝑒 𝐻𝑒𝑎𝑙 • If 𝑁𝑒𝑎𝑟ℎ𝑜𝑙𝑒 & 𝑛𝑖 ∉ 𝑃𝑘𝑡. 𝑝𝑎𝑡ℎ & 𝑃𝑘𝑡. 𝑠𝑟𝑐 ≠ 𝑛𝑖 & (∄𝐿𝑛𝑘 𝑛𝑖,𝑃𝑘𝑡.𝑃𝑎𝑡ℎ 𝑖−1 || ∄𝐿𝑛𝑘_(𝐻𝑐, 𝑃𝑘𝑡. 𝑃𝑎𝑡ℎ𝑖−1)) – If (𝑃𝑘𝑡. 𝑑𝑠𝑡 2 ) > 𝐷𝑖𝑠𝑡 (𝐶𝑝𝑜𝑠 𝑥,𝑦 & (𝑥 𝑛𝑖 , 𝑦 𝑛𝑖 )) Set 𝐹𝑢𝑡𝑢𝑟𝑒 𝑝𝑜𝑠 ← 𝐶𝑝𝑜𝑠 𝑥,𝑦+ (𝑥 𝑛 𝑖 ,𝑦 𝑛 𝑖 ) 2 𝑀𝑜𝑣(𝐹𝑢𝑡𝑢𝑟𝑒 𝑝𝑜𝑠) – 𝑅𝑒𝑏𝑟𝑜𝑎𝑑𝑐𝑎𝑠𝑡(𝑃𝑘𝑡) • Else if – If ! 𝑁𝑒𝑎𝑟ℎ𝑜𝑙𝑒 & 𝑛𝑖 ∉ 𝑃𝑘𝑡. 𝑝𝑎𝑡ℎ & 𝑃𝑘𝑡. 𝑠𝑟𝑐 ≠ 𝑛𝑖 & ∄𝐿𝑛𝑘_(𝑛𝑖, 𝑃𝑘𝑡. 𝑃𝑎𝑡ℎ𝑖−1. 𝐹𝑡𝑟𝑥,𝑦) 𝑀𝑜𝑣𝑒_(100 → 𝑃𝑘𝑡. 𝑃𝑎𝑡ℎ𝑖−1) • Else – 𝐹𝑟𝑒𝑒(𝑝𝑘𝑡) 4) If Node 𝒏𝒊′𝒔 𝑻𝒊𝒎𝒆𝒓 𝑵𝒆𝒊𝒈. 𝒆𝒙𝒑𝒊𝒓𝒆𝒅 – For each 𝑴 ∈ 𝑻𝒃𝒍 𝑵 • If 𝑀. 𝑇𝑒𝑥 < 𝑇𝑛𝑜𝑤 – Set 𝐼𝑑𝑓𝑎𝑖𝑙 = 𝑀. 𝐼𝑑 – 𝐷𝑒𝑙𝑒𝑡𝑒(𝑀) • 𝑇𝑖𝑚𝑒𝑟 𝐻𝑜𝑙𝑒 𝑑𝑖𝑠𝑐 . 𝑆𝑐ℎ𝑒𝑑𝑢𝑙𝑒(𝑇𝑛𝑜𝑤 + 𝑇𝑅𝑎𝑛𝑑) – 𝑆𝑐ℎ𝑒𝑑𝑢𝑙𝑒(𝑇𝑛𝑜𝑤 + 𝑇𝑅𝑎𝑛𝑑) 5) Node 𝒏𝒊′𝒔 If 𝑇𝑖𝑚𝑒𝑟 𝐻𝑜𝑙𝑒 𝑑𝑖𝑠𝑐 .expired – Generate 𝑝𝑘𝑡 • 𝑀𝐷𝑖𝑠𝑡𝑓𝑎𝑖𝑙 = 0 • 𝑛𝑖 → 𝑝𝑘𝑡. 𝑠𝑟𝑐 • 𝑝𝑘𝑡. 𝑡𝑦𝑝𝑒 = 𝐻𝑜𝑙𝑒 𝑑𝑖𝑠𝑐 • (𝑥 𝑛𝑖 , 𝑦𝑛𝑖 ) → 𝑝𝑘𝑡. 𝑆𝑝𝑜𝑠 • 𝑛𝑖 → 𝑝𝑘𝑡. 𝑝𝑎𝑡ℎ • 𝐼𝑛𝑖𝑡 (𝑝𝑘𝑡. ℎ𝑜𝑝 & 𝑝𝑘𝑡. 𝐶𝑝𝑜𝑠) – 𝑏𝑟𝑜𝑎𝑑𝑐𝑎𝑠𝑡(𝑝𝑘𝑡) 6) If 𝑇𝑖𝑚𝑒𝑟 𝐻𝑜𝑙𝑒 𝐻𝑒𝑎𝑙 . 𝑒𝑥𝑝𝑖𝑟𝑒𝑑 in Node 𝒏𝒊 – Generate 𝑃𝑘𝑡 • 𝑃𝑘𝑡. 𝑠𝑟𝑐 = 𝑛𝑖 • (𝑥 𝑐, 𝑦𝑐) → 𝑃𝑘𝑡. 𝐶𝑝𝑜𝑠 • 𝑀𝐷𝑖𝑠𝑡𝑓𝑎𝑖𝑙 → 𝑃𝑘𝑡. 𝑑𝑠𝑡 • 𝑃𝑘𝑡. 𝑡𝑦𝑝𝑒 = 𝐻𝑜𝑙𝑒 𝐻𝑒𝑎𝑙 – 𝑏𝑟𝑜𝑎𝑑𝑐𝑎𝑠𝑡(𝑃𝑘𝑡) 3.2 Pre-Failure Controller Let, 𝐸𝑐 for Current energy level, 𝐸 𝑇ℎ for threshold energy level, 𝐿 𝑐𝑟𝑖𝑡𝑖𝑐 for critical node list, 𝐿 𝐸𝑥𝑎𝑐𝑡 for Available Extra actor list, 𝐼𝑑 𝐸𝑥 for Extra actor Id, 𝑃𝑜𝑠 for postion, 1) If 𝐸𝑐 < 𝐸 𝑇ℎ a. Generate 𝑃𝑘𝑡. 𝑐𝑟𝑖𝑡𝑖𝑐𝑎𝑙 b. 𝑃𝑘𝑡. 𝑁𝑑 = 𝑁𝑖𝑑 c. Broadcast 𝑃𝑘𝑡 2) If 𝑃𝑘𝑡 recv in 𝑁 a. If 𝑝𝑘𝑡 is Duplicate i. Free 𝑃𝑘𝑡 ii. 𝑅𝑒𝑡𝑢𝑟𝑛 b. If 𝑃𝑘𝑡. 𝑐𝑟𝑖𝑡𝑖𝑐𝑎𝑙 i. If 𝑁 ≠ 𝐵𝑆 1. Rebroadcast 𝑃𝑘𝑡 ii. If 𝑁 = 𝐵𝑆 1. 𝑃𝑘𝑡. 𝑁𝑑 ∪ 𝐿 𝑐𝑟𝑖𝑡𝑖𝑐 2. If 𝐿 𝐸𝑥𝑎𝑐𝑡 ≠ 𝑁𝑢𝑙𝑙 a. 𝐼𝑑 𝐸𝑥 = 𝐿 𝐸𝑥𝑎𝑐𝑡(1) b. 𝑅𝑒𝑎𝑟𝑟𝑎𝑛𝑔𝑒(𝐿 𝐸𝑥𝑎𝑐𝑡) c. 𝑀𝑜𝑣𝑒(𝐼𝑑 𝐸𝑥 → 𝐿 𝐶𝑟𝑖𝑡𝑖𝑐(1). 𝑃𝑜𝑠) d. 𝑅𝑒𝑎𝑟𝑟𝑎𝑛𝑔𝑒(𝐿 𝐶𝑟𝑖𝑡𝑖𝑐) c. If 𝑃𝑘𝑡. 𝐸𝑥𝑎𝑐𝑡 𝑎𝑟𝑟𝑖𝑣𝑒 i. If 𝑁 ≠ 𝑁𝑑 𝐶𝑟𝑖𝑐𝑎𝑙 1. 𝐼𝑔𝑛𝑜𝑟𝑒(𝑃𝑘𝑡) 2. 𝑟𝑒𝑡𝑢𝑟𝑛
- 4. International Journal of Computer Applications Technology and Research Volume 4– Issue 12, 923 - 927, 2015, ISSN: 2319–8656 www.ijcat.com 926 ii. 𝑆𝑤𝑖𝑡𝑐ℎ 𝑛𝑒𝑖𝑔ℎ(𝑁 → 𝐼𝑑 𝐸𝑥) iii. 𝑀𝑜𝑣𝑒(𝑁 → 𝐵𝑆. 𝑝𝑜𝑠) 4. REQUIREMENTS Hardware: Single PC with 20 Gb Hard disc space 1Gb RAM Software: Linux OS (Ubuntu 10.04), NS2.34 Languages: TCL (Front end type project only), C++ (Optional) Result We have tested our output with ns2 simulator and we got a two results, one is NAM, Xgraph. Our enhancement method provides best results such as no node failure and less movement. Fig. A1 Network placement and sensing area Fig. A2 Hole detection Fig. A3 Hole healing Fig.A4 Graph for avg moving distance Fig.A5 Node failure
- 5. International Journal of Computer Applications Technology and Research Volume 4– Issue 12, 923 - 927, 2015, ISSN: 2319–8656 www.ijcat.com 927 Fig.A6 Node movement 5. CONCLUSION The Mobile Wireless Sensor Network is the emerging solution for monitoring of a specified region of interest. Several anomalies can occur in WSNs that impair their desired functionalities resulting in the formation of different kinds of holes, namely: coverage holes, routing holes. Our ultimate aim is to cover total area without coverage hole in wireless sensor networks. We propose a comprehensive solution, called holes detection and healing. We divided our proposed work into two phases. The first phase consists of three sub- tasks; Hole- identification, Hole-discovery and border detection. The second phase treats the Hole-healing with novel concept, hole healing area. It consists of two sub-tasks; Hole healing area determination and node relocation. 6. REFERENCES 1) Taeyoung Kim,1 Minhan Shon,1 Mihui Kim,2 Dongsoo S. Kim,3 and Hyunseung Choo1 “Anchor-Node-Based Distributed Localization with Error Correction in Wireless Sensor Networks”, 2012 2) “Accurate Anchor-Free Node Localization in Wireless Sensor Networks” Adel Youssef, Ashok Agrawala and Mohamed Younis. 3) “Movement-Assisted Sensor Deployment” Guiling Wang, Guohong Cao, and Tom La Porta. 4) “Movement Control Algorithms for Realization of Fault-Tolerant Ad Hoc Robot Networks” Prithwirh Basu and Jason Redi. 5) K. Akkaya, F. Senel, A. Thimmapuram, and S. Uludag, “Distributed recovery from network partitioning in movable sensor/actor networks via controlled mobility,” IEEE Trans. Comput., vol. 59, no. 2, pp. 258–271, Feb. 2010. 6) K. Akkaya and M. Younis, “COLA: A coverage and latency aware actor placement for wireless sensor and actor networks,” in Proc. IEEE VTC, Montreal, QC, Canada, Sep. 2006, pp. 1–5. 7) A. Youssef, A. Agrawala, and M. Younis, “Accurate anchor-free localization in wireless sensor networks,” in Proc. 1st IEEE Workshop Inf. Assurance Wireless Sensor Netw., Phoenix, AZ, Apr. 2005. 8) S. Vemulapalli and K. Akkaya, “Mobility-based self route recovery from multiple node failures in mobile sensor networks,” in Proc. 10th IEEE Int. Workshop WLN, Denver, CO, Oct. 2010. 9) S. Yang, M. Li, and J. Wu, “Scan-based movement- assisted sensor deployment methods in wireless sensor networks,” IEEE Trans. Parallel Distrib. Syst., vol. 18, no. 8, pp. 1108–1121, Aug. 2007. 10) G. Wang, G. Cao, and T. La Porta, “Movement-assisted sensor deployment,” IEEE Trans. Mobile Comput., vol. 5, no. 6, pp. 640–652, Jun. 2006.