Bee Inspired Routing Protocol Using Lossless Compression Based On Swarm Technology

Volume 8, No. 5, May-June 2017

International Journal of Advanced Research in Computer Science RESEARCH PAPER

Available Online at www.ijarcs.info

ISSN No. 0976-5697

Bee Inspired Routing Protocol Using Lossless Compression Based On Swarm

Technology

Er.Sumeet Pal

M.Tech Scholar, Department of Computer Science & Engineering,

Guru Nanak Dev University, RC Campus Jalandhar, India

Er.VarinderKaur Attri

Assistant Professor, Department of Computer Science & Engineering,

Guru Nanak Dev University, RC Campus Jalandhar, India

Abstract: This paper has introduced on swarm Intelligence Swarm Intelligence based redirecting standards specifically Bee-Inspired dependent redirecting standards with regard to offering multipath routing in Wireless ad hoc networks (WANETs). WANETs impact a great agent-based protocol which specifies several procedures as well as that many the actual contributing nodes follow. By utilizing this method, nodes will be connected with each other and so on that basis it lowers computational as well as resource costs. Swarn Intelligence uses agent-like agencies from insect's cultures for being metaphor. But belief that Bee-Inspired hasn’t utilized compression algorithm so that it can take advantage of the bandwith in efficient way. Hence this document offered LCBEEIP standard protocol which is desired BEEIP standard protocol using lack of lossless compression. The actual experimental effects has shown that this consist of approach currently have obviously observed the fact that consist of approach outperforms above the most recent methods. The proposed approach has obtained approximately 99.9167 percentages.

Keywords: Wireless sensor network, Bee inspired routing protocol, Compression techniques, Swarm intelligence

I. INTRODUCTION

A Wireless Sensor Network is a self-configuring network which composes of small sensor nodes communication through signals of radio, monitor etc. Included within these networks are base station and sinks. Various functions are portrait through these sensors, such as data sensing, transmission of the data, information processing etc. Collecting and forwarding information is done through the base station. Sensor nodes have the ability to sense and process the data. Low-cost sensors are included in the WSNs, which are intelligent in nature, therefore, are now replacing traditional networks in many scenarios. Many others reasons would include increases data transmission, deployment easiness and self-organization behavior. Fig 1 shows an essential sensor network with 3 nodes. Node1 and node3 are not going to be within collection of one other; however node2 will help you forward packets between node1and node2. The node2 will undoubtedly is a router these three nodes together form a network. [8]

Fig 1: Wireless Network with different nodes

1.1 BEEIP Routing Protocol

It is really a new redirecting protocol encouraged by honeybee with respect to the mutual behaviors of honeybee

foragers [21]. That redirecting protocol is applied when data will be distributed involving the nodes. The key intent behind that BEEIP redirecting protocol would be to check and gauge the efficiency with the found routes and pick the most effective one in accordance with variety system. That conveys the capability of honeybees to perform the foraging as well as talk together, to have successful recruitment. That BEEIP redirecting protocol is truly applied to locate numerous routes involving the resources and the places and also spread the traffic across them in a well-organized way. 1.1.1 Adaptive Scouting

Adaptive scouting when there's essential of a option between the origin and the location, a search box is done and delivered by transmitted to the complete of the network. That search box reports for locating uncommitted approach to their location [22]. If the required sink is the expected final, an ack_scout box is made as well as delivered support again to the origin sink to guarantee the effective routes. A location node is preparing to build numerous ack_scout, dependant on a number of scouts it gets within the system, letting numerous routes if you are discovered.

1.1.2 Adaptive Foraging

2. TECHNIQUES USED

2.1 Compression Techniques

Compacted details could be transported usually by way of a couple of procedures: i.e. sending practice along with obtaining process. The position of your emailer practice would be to initially constrict the last results after which this send out this car communication network. Otherwise, a radio practice gets a squeezed details and also decompresses it. The data compresion technique is one which could be utilized to cut back carried knowledge around instant channels. That method contributes to a lowering of the necessary inter-node conversation, which will be the key energy use in wireless networks [7]. Data compression techniques might be defined into two various ways i.e. A. Lossy Methods

B. Lossless Methods 2.1.1 Lossless compression

In lossless data compression, the value of information is preserved. The main information as well as the information after compression and decompression is same since, with this technique, the retention as well as decompression formulations are common of each and every various: knowledge is disoriented in the process. The absolute most normal sort of lossless force is Lempel Ziv Encoding. Lempel Ziv (LZ) progress is definitely an model of a credit card application of formulations called dictionary-based encoding.

2.2 Swarm Intelligence

It is truly a man-made intelligence (AI) technique in accordance with the collective behavior in decentralized, self-organized systems. This is a great exploration about ‘ants'conduct during which several ants are usually impaired and communicating entirely relies on use regarding substances just like ingredient commonly known as pheromones, created throughout the ants and lodged into the pathways when walking searching for meals [10]. With the use of this sensing pheromone trail forgers can discover their paths to food which is discovered by other ants. The most widely used illustration of swarm intelligence method is definitely the Swarm of Bees. The most frequent SI Algorithms are:

a) Ant Colony Optimization

Ant Colony Optimization is principally a routing algorithm particularly helpful to discover shortest path between two nodes. Ants have applied successful routing o determine shortest path between their food sources and nest that includes pheromone trail laid through another ants. This is called as a stigmergy and Ant Colony Optimization routing . ACO is simply a swarm intelligence based optimization technique whose main objective is often to establish the shortest route among the main sender node and the base station for maximizing the network lifetime.

b) Particle Swarm Optimization

Particle swarm optimization (PSO) is usually some sort of populace dependent stochastic search engine optimization procedure that was encouraged by social behavior. PSO optimizes the disorder simply through a population of candidate solutions. This particle's placement plus rate is defined inside of referred to as allergens by way of moving these types of allergens inside of look for space banking on straightforward numerical formulae. Every particle's movement is integrated by its local recognized location

moreover, mainly focused around the most widely position inside the search space which ends up like a stronger position discovered by another particles. An efficient variant within the PSO algorithm is work upon the population of the candidate solution that is considered a particle's. These particles are moving along the search-space relying on simple formulae. A motions inside allergens is actually handled by way of their particular most common position into the search-space along with the total swarm's most popular position.

C) Artificial Bee Colony Optimization

In the ABC product, a nest entails some multiple bees: applied bees, viewers and also scouts [14]. It's actually implicit which we have an particular person unnatural applied bee intended for virtually any foods source. Utilised bees obtain utilizing food and also examine hive and also bash to the picture. The used bee whose food supply is forgotten becomes a search and begins to find out a fresh food source. Onlookers view the dances of used bees as well as pick food options pushed by dances. Synthetic Bee Colony (ABC) is actually among lately described formulas which were determined through the sensible conduct of baby bees. ABC similarly a 1 optimization software created by applying a| populace centered research treatment whereby people are meals roles are altered through the synthetic bees set along with bee's goal with the recent areas of food options with excellent nectar volume last of all most usually the one with the most effective nectar.

3. RELATED WORK

Swarm Direction-finding Method for Cell Offer Hoc Networks. Dengiz, Orhan ,et al.(2011)[7]proposed a vibrant mobile phone advert hoc circle (MANET) managing process to increase circle connection by using handled circle nodes, known as agents. A chemical travel search engine marketing (PSO) protocol works by using the ideal move purpose to pick optimum spots on the realtors during every time stage with circle operation. The proposed MANET managing technique are cautiously tested in several interferance as well as vibrant problems. Computational final results reveal that a proposed approach is effective in improving the connectivity of MANETs and predicting movements of user nodes and deploying agents accordingly significantly improves the overall performance of a MANET.Saleem, Muhammad avec al. (2011) [8] have a survey across the Swarm Brains which often relies in nav protocol for wifi alarm communities. The majority of the study in swarm intelligence has centered on opposite executive in addition to version of combined behaviors experienced in normal methods with the goal of planning powerful formulas for spread optimization. Ali, Zulfiqar, et al.(2011)[9]Designed evolutionary solutions including anatomical programming (GP), Neural Circle, Evolutionary programming (EP), Compound Swarm Seo (PSO) plus Ould like Nest Seo (ACO) employed for this redirecting protocols inside advertising hoc plus sensor / probe wifi networks. You will find constraints involved in these protocols due to the mobility and non infrastructure nature of an ad hoc and sensor networks. We study in this research work a probabilistic performance evaluation frameworks and Swarm Intelligence approaches (PSO, ACO) for routing protocols.Waseem M., et al. (2011) [10] presented a creative crossbreed chemical travel search engine marketing technique, termed Linearly Decreasing Bodyweight Imply PSO, can be suggested, in line with the idea with mixing the link between linearly decreasing excess fat with the straight line collaboration of such a couple of initial conditions with all the swiftness formula. Zhang, Fengyuan, et al. (2011) [11] analyzes LZW algorithm to compress the bridge vibrations data when using the heap of the most current technique called forward-moving is scheduled onto frequently-used entries. Adamu Murtala Zungeru et al. (2012) [12]presented a survey on SI based routing protocol for WSN and in addition did an evaluation between different routing protocols. Firstly, it represents a surveys on state-of-the-art routing protocols in WSNs from classical routing protocols to swarm intelligence based protocols. Santhiya, K. G., et al. (2012) [13] introduces the current general framework to get obtaining QoS this provides a group primarily based nav and also pertains Manufactured Bee Nest marketing to get efficient ideal option uncovering throughout MANET. This utilizes a basic principle of combined thinking ability and also victory of unnatural honey bees. Shirkande, Sudarshan D., et al (2013) [14] presented survey on ACO based nav algorithms regarding MANETs. Ant Nest protocol will be prompted by self-organizing actions regarding little bugs who go together with Swarm Intelligence. Market research will be attained about different insect nest based nav algorithms regarding Cellular Warning system (WSN) plus Cell phone Ad-Hoc Network (MANETs). Sharma, Dhirendra Kumar, et al. (2013) [15] analyzed the latest technique for intra and inters cluster routing in numerous scenarios. The proposed

algorithm takes the key components of proactive and reactive routing protocols. Kiatwuthiamorn, Jiraporn, et al. (2013) [16] proposed the latest optimization technique depending on the natural behavior of the ant colonies.

Through this proposed protocol, a foraging behavior with employee helpless ants is utilized with regard to in the area looking for much better alternative although wedding, mating, plus feeding habits usually are working at replica with the modern generation. Asaju la ARO Bolaji, et al. (2013) [17] presented the ABC algorithm. Artificial Bee Colony Algorithm (ABC) is nature-inspired Meta heuristic, which imitates the foraging behavior of bees. Rufai, Awwal Mohammed, et al. (2013) [18] proposed a fresh lossy compression technique by using a singular value decomposition (SVD) associated with Huffman coding. Firstly the design and style is decomposed by using SVD thin rank is reduced by ignoring the majority of the lower singular values and rows of hanger and aligner matrices. Nandi, Utpal, et al. (2013) [19] consist of any lossless dictionary-based details data compresion procedure based on modified data compresion procedure devoted to optimality regarding LZW rule (OLZW).The encoding strategy of lossless details data compresion is really a competing while using OLZW. Aarti, Dr S.S Tyagi, et al. (2013) [20] looks at portable ad-hoc multilevel in addition to features, difficulties, program, security ambitions together with type's security episodes at diverse layers. Mobile sensor systems (MANETs) will be a infrastructure-less, strong multilevel contains several wi-fi portable nodes which speak alongside one another while not having to work with almost any dierected authority.John, Jomy, and R. Pushpalakshmi et al. (2014) [21] focused on the optimization of energy consumption and stability within the node which has evolved into critical issue in sensor networks. Clustering of nodes has become the significant way to boost the utilization of the network. Vanthana, S., and V. Prakash, (2014) [22] presented evaluation based on performance metrics i.e. throughput, packet loss and end-to-end delay, along with the simulator used is NS-2 in Ubuntu operating system (Linux).

4. EXPERIMENTATION AND ANALYSIS OF RESULTS

4. Proposed Methodology

1. Initialize society together with unique solutions. 2. Consider exercise of the inhabitants.

3. Even though creating completely new people. 4. Opt for web sites for neighborhood WANETS node. 5. Generate bees for picked web pages (more bees for the very best e sites) and approximation fitness's.

6. Opt for the fittest bee via every node repair.

7. Set aside left over bees so that you can WANETS node aimlessly and also estimate their own fitness's.

8. End While

Fig 2: Proposed Methodology

4.2 Performance Analysis

That paper has got fashioned along with integrated this suggested strategy in MATLAB tool u2013a. That paper includes a number of boundaries i.e. management cost, end-to-end hesitate, throughput, box shipping and delivery ratio. Overview is driven amongst all the boundaries along with a particular furniture along with figure exhibits all the results by employing vicinity (x, y) i.e. 100, 100 along with nodes varying coming from 100-1000 by using message sizing 4000 bits.

Initial Environment: On applying artificial bee colony optimization, following results will be achieved.

Fig 3: Sensor Nodes Environment

Fig.3: shows a squared area of sensor network having diameter as 100/100m in which ABC algorithm is applied where stars designated as number of sensor nodes and diamond designate as base station and blue lines shows the communication between the sensor nodes.

Proposed Environment: On applying artificial bee colony optimization with the feature of Lossless Data compression, following results will be achieved.

Fig 4: Depicting Mobility of Nodes

Fig 4: shows a squared area of sensor network having diameter as 100/100m in which ABC algorithm is applied and also applies lossless data compression method where stars designated as number of sensor nodes and diamond designate as base station and blue lines shows the communication between the sensor nodes.

1. Control Overhead: Overhead is virtually any blend of overburden or otherwise strong computation time, reminiscence, information, and additional options that contain in order to have a unique objective. Fig.3exhibits your contrast with Management Over head in between existing plus the planned technique. In this case your planned expense are fairly under your Giagkos & Wilson technique [13].

Fig.5: Control Overhead

Fig 6: End To End Delay

3. Throughput:Ordinarily terminology, throughput is definitely the velocity of creation or even the velocity where anything is usually processed. Fig.7 reveals a assessment of throughput involving established plus the offered procedure Inside our scenario a offered throughput is definitely better versus Giagkos & Wilson method [13].

Fig 7 : Throughput

4. Packet Delivery Ratio: Greater valuation of packet shipping and delivery rate reveals the better performance. It can be named the actual ∑ Degree of packet obtain / ∑ Degree of packet send. Fig 7 reveals the actual contrast involving PDR involving active along with the offered technique. In your instance the actual offered perform has demonstrated 0.07% advancement in comparison with Giagkos & Wilson strategy [13] with regards to PDR.

Fig 8: Packet Delivery Ratio

5. CONCLUSION

It represents about Swarm intelligence primarily based route-finding networks specifically Bee-Inspired

direction-finding diet that gives multipath routing. Though considering the Bee-Inspired direction-finding has never applied retention strategy by simply when using the data transfer rate within powerful way. Consequently, the actual LCBEEIP can be proposed which usually employs BEEIP diet using the products Reduction Fewer information compression. That document possesses drawn the actual contrast in the proposed strategy using established approaches to the part involving right after boundaries i.e. end-to-end delay, control overhead, packet delivery ratio, throughput. The comparisons has displayed that the effectiveness of the proposed method outperforms prevailing one. The proposed method possesses reached approximately 99.9167 box distribution relative amount which was 99.27 in case of BEEP protocol.

6. REFERENCES

[1] Shukla, Jaya, Manoj Alwani, and Anil Kumar Tiwari. "A survey on lossless image compression methods."

[2] Gautam, Sumanlata, "Swarm Routing Protocol for Mobile Ad Hoc Networks", Advances in Computing, Control and Telecommunication Technologies (ACT), 2010 Second International Conference on. IEEE, 2010

2010 2nd International Conference on Computer Engineering and Technology. 2010.

[3] Mohseni, Shima, et al. "Comparative review study of reactive and proactive routing protocols in MANETs."

[4] Sultanov, Hakim, and Jane Huffman Hayes. "Application of swarm techniques to requirements engineering:Requirements tracing."

Digital Ecosystems and Technologies (DEST), 2010 4th IEEE International Conference on. IEEE, 2010.

[5] Villalba, LJ García, Delfín Rupérez Cañas, and Ana Lucila Sandoval Orozco, "Bio- inspired routing protocol for mobile ad hoc networks."

Requirements Engineering Conference (RE), 2010 18th IEEE International. IEEE, 2010.

[6] Rahman, Md Arafatur, et al. "A simulation based performance comparison of routing protocol on Mobile Ad-hoc Network (proactive, reactive and hybrid)."Computer and Communication Engineering (ICCCE), 2010 International Conference on. IEEE, 2010.

IET communications4.18 (2010): 2187-2195

[7] Dengiz, Orhan, Abdullah Konak, and Alice E. Smith. "Connectivity management in mobile ad hoc networks using particle swarm optimization." Ad Hoc Networks

[8] Saleem, Muhammad, Gianni A. Di Caro, and Muddassar Farooq, "Swarm intelligence based routing protocol for wireless sensor networks: Survey and future directions."

9.7 (2011): 1312-1326.

Information Sciences

[9] Ali, Zulfiqar, and Waseem Shahzad. "Critical analysis of swarm intelligence based routing protocols in adhoc and sensor wireless networks." In

181.20 (2011): 4597-4624.

[10] Chandrasekhar, U., and P. R. P. Naga. "Recent trends in ant colony optimization and data clustering: A brief survey." In

Computer Networks and Information Technology (ICCNIT), 2011 International Conference on, pp. 287-292. IEEE, 2011.

[11] Zhang, Fengyuan, et al. "Implementation and optimization of LZW compression algorithm based on bridge vibration data."

Intelligent Agent and Multi-Agent Systems (IAMA), 2011 2nd International Conference on, pp. 32-36. IEEE, 2011.

Procedia Engineering

[12] Poongkuzhali, T., V. Bharathi, and P. Vijayakumar. "An optimized power reactive routing based on AODV protocol for Mobile Ad-hoc network."

15 (2011): 1570-1574.

[13] Tan, Swee Chuan, Kai Ming Ting, and Shyh Wei Teng. "Simplifying and improving ant-based clustering." Procedia Computer Science

[14] Alhasan, Waseem M., et al. "LDW Mean PSO: A new improved particle swarm optimization technique."

4 (2011): 46-55.

[15] Adamu Murtala Zungeru, Li-Minn Ang, Kah Phooi Seng, “Classical and swarm intelligence based routing protocols for wireless sensor networks: A survey and comparison,"

Computer Engineering Conference (ICENCO), 2011 Seventh International. IEEE, 2011.

Journal of Network and Computer Applications

[16] Dhivya, M., and M. Sundarambal. "Lifetime Maximization in Wireless Sensor Networks using Tabu Swarm Optimization."

35, (2012): 1508-1536.

Procedia Engineering

[17] Santhiya, K. G., and N. Arumugam. "A novel adaptive bio-inspired clustered routing for MANET."

38 (2012): 511-516.

Procedia Engineering

[18] Mahmudimanesh, Mohammadreza, Abdelmajid Khelil, and Neeraj Suri. "Balanced spatio-temporal compressive sensing

30 (2012): 711-717.

for multi-hop wireless sensor networks."

[19] Ismail, Nurul Halimatul Asmak, and Rosilah Hassan. "6LoWPAN local repair using bio inspired artificial bee colony routing protocol."

Mobile Adhoc and Sensor Systems (MASS), 2012 IEEE 9th International Conference on. IEEE, 2012.

[20] Gupta, Kunal, Mukesh Sharma, and Parmanand Sharma. "Lossless compression based Kmp technique."

Procedia Technology11 (2013): 281-287.

[21] Ramamoorthy, H. Vignesh, and H. Karthikeyani. "Hybrid routing scheme of multi agent ant based system in MANET combination of proactive and reactive."

Optimization, Reliabilty, and Information Technology (ICROIT), 2014 International Conference on. IEEE, 2014.

[22] Alexandros Giagkos, and Myra S. Wilson, "BEEIP –Swarm Intelligence based routing for wireless ad hoc networks",

Information Communication and Embedded Systems (ICICES), 2014 International Conference on. IEEE, 2014.