Leveraging SPOON

Download Full-Text PDF Cite this Publication

Text Only Version

Leveraging SPOON

Vijayakumar C Mtech student, Department of CSE,

AMC Engineering college, Bangalore

Shalini S Assistant Professor, Department of CSE

AMC Engineering college, Bangalore

Abstract: Current distributed (P2P) file sharing methods in mobile ad-hoc networks (MANETs) can be arranged into three gatherings: flooding-based, advertisement based, and social contact-based. In flooding-based methods, 7DS is one of the first approaches to port P2P technology to mobile environments. It exploits the mobility of nodes within a geographic area to disseminate web content among neighbors. Passive distributed indexing (PDI) is a general-purpose distributed file searching algorithm. It uses local broadcasting for content searching and sets up content indexes on nodes along the reply path to guide subsequent searching. In advertisement based methods, the has to inform their requirements to its neighbor nodes, it leads to high overhead.therefor the initial two gatherings of routines can be easily have high overhead and low adaptability. They are essentially produced for connected MANETs, in which end-to- end network among nodes is guaranteed. The third gathering of techniques are mainly for disconnected MANETs however it fails to consider the social interests of mobile hubs, which can be misused to improve the file searching efficiency. In this paper, we propose a P2P content based document imparting framework, in particular SPOON, for disconnected MANETs. The framework utilizes an interest extraction calculation to get a nodes advantage from its records for content based file searching. For efficient file searching, SPOON bunches regular interesting nodes and groups the frequently visiting nodes. It exploits node versatility by assigning stable nodes, which have the most regular contact with group individuals, as group facilitators for intercommunity looking, and the nodes that visit other communities are called ambassadors for intercommunity seeking. An interest-oriented scheme is proposed to improve file searching efficiency. File searching efficiency. Additional improvements like file prefetching, querying-completion, and loop- prevention are the consideration for further enhancement.

KEYWORDS: MANETS, CONTENT-BASED FILE SHARING, SOCIAL NETWORKS.

  1. INTRODUCTION

    From past few years, cell phones, for example, laptops, PDAs, and cell phones have been playing an important role. In reality, the quantity of cell phone clients expanded by 118 million over the world in 2007 [1], and is relied upon to stretch around 300 million by 2013 [2]. The unbelievably fast development of versatile clients is prompting a promising

    future, in which they can uninhibitedly impart records between one another at whatever point and wherever. The quantity of versatile seeking clients (through cell phones, highlight telephones, tablets, and so forth.) is evaluated to achieve 901.1 million in 2013 [3]. Presently, versatile clients associate with one another and offer documents by means of a base structured by geologically circulated base stations. Notwithstanding, clients may end up in a range without remote administration (e.g., mountain ranges and provincial territories). Also, clients may plan to decrease the expense on the costly foundation system information.

    The P2P document imparting model makes extensive scale arranges a gift rather than a condemnation, in which hubs offer documents specifically with one another without an incorporated server.

    In MANETs consisting of digital devices, nodes are constantly moving, forming disconnected MANETs with opportunistic node encountering. Such transient network connections have posed a challenge for the development of P2P MANETs. Traditional methods supporting P2P MANETs are flooding-based [6], [7], [8], [9] or

    advertisement-based [10], [11], [12].

    The former methods rely on flooding for file searching. However, they lead to High overhead in broadcast. In the latter methods, nodes advertise their available files, build content tables, and forward files according to these tables.

    Some researchers [13], [14], [15], [16], [17] further proposed to utilize cache/replication to enhance data dissemination/access efficiency in disconnected MANETs. However, nodes in these methods passively wait for contents that they are interested in rather than actively search files, which may lead to a high search delay.

    Recently, social networks are exploited to facilitate content dissemination/publishing in disconnected MANETs [18], [19], [20], [21]. These methods exploit below property to improve the efficiency of message forwarding:

    (P1) nodes (i.e., people) usually exhibit certain movement patterns (e.g., local gathering, diverse centralities, and skewed visiting preferences).

    However, these methods are only for the dissemination of information to subscribers. They are not specifically designed for file searching. Also, they fail to take into account other properties of social networks revealed by recent studies to facilitate content sharing:

    (P2) Users usually have a few file interests that they visit frequently [22] and a users file visit pattern follows a power- law distribution [23].

    (P3) Users with common interests tend to meet with each other more often than with others [24].

    By leveraging these properties of social networks, we propose social network-based P2P content-based file sharing in disconnected mobile ad hoc Networks (SPOON) with four components as shown in Fig. 1:

    1. Based on P2, we propose an interest extraction algorithm to derive a nodes interests from its files. The interest facilitates queries in content-based file sharing and other components of SPOON.

    2. We refer to a collective of nodes that share common interests and meet frequently as a community. According to P3, a node has high probability to find interested files in its community. If this fails, based on P1, the node can rely on nodes that frequently travel to other communities for file searching. Thus, we propose the community construction algorithm to build communities to enable efficient file retrieval.

    3. According to P1, we propose a node role assignment algorithm that takes advantage of node mobility for efficient file searching. The algorithm designates a stable node that has the tightest connections with others in its community as the community coordinator to guide intercommunity searching. For each known foreign community, a node that frequently travels to it is designated as the community ambassador for intercommunity searching.

    We propose an interest-oriented file searching and retrieval scheme that utilizes an interest-oriented routing algorithm (IRA) and above three components. Based on P3, IRA selects forwarding node by considering the probability of meeting interest keywords rather than nodes. The file searching scheme has two phases: Intra- and intercommunity searching. In the former, a node first queries nearby nodes, then relies on coordinator to search the entire home community. If it

    fails, the intercommunity searching uses an ambassador to send the query to a matched foreign community. A discovered file is sent back through the search path or the IRA if the path breaks.

    SPOON is novel in that it influences informal organization properties of both hub investment and development design. Initially, it arranges basic investment and oftentimes experienced hubs into social groups. Second, it considers the recurrence at which a hub meets distinctive hobbies instead of diverse hubs in document seeking. Third, it picks stable hubs in a grou as facilitators and exceptionally portable hubs that travel regularly to outside groups as envoys. Such a structure guarantees, to the point that an inquiry can be sent to the group of the questioned document rapidly. SPOON likewise fuses extra methodologies for record prefetching, questioning fruition and circle aversion, and hub beat thought to further improve document seeking effectiveness.

    Whatever is left of the paper is masterminded as takes after: Section 2 gives a review of related works. Area 3 exhibits the configuration of the parts of SPOON. In Section 4, the execution of SPOON is assessed in correlation with different frameworks. The last segment presents closing comments and future work.

  2. RELATED WORK

    1. P2P File Sharing in MANETs

      We first introduce the P2P file sharing algorithms designed in MANETs.

      1. Flooding-Based Methods

        In flooding-based methods, 7DS [6] is one of the first approaches to port P2P technology to mobile environments. It exploits the mobility of nodes within a geographic area to disseminate web content among neighbors. Passive distributed indexing (PDI) [8] is a general-purpose distributed file searching algorithm. It uses local broadcasting for content searching and sets up content indexes on nodes along the reply path to guide subsequent searching. Klemm et al. [7] proposed a special-purpose on-demand file searching and transferring algorithm based on an application layer overlay network. The algorithm transparently aggregates query results from other peers to eliminate redundant routing paths.

        Hayes [9] extended the Gnutella system to mobile environments and proposed the use of a set of keywords to represent user interests.

        However, these flooding-based methods produce high overhead due to broadcasting.

      2. Advertisement-Based Methods

        Tchakarov and Vaidya [10] proposed GCLP for efficient content discovery in location-aware ad hoc networks. It disseminates contents and requests in crossed directions to ensure their encountering. P2PSI [11] combines both advertisement (push) and discovery (pull) processes. It adopts the idea of swarm intelligence by regarding shared files as food sources and routing tables as pheromone. Each file holder regularly broadcasts an advertisement message to inform surrounding nodes about its files. The discovery process locates the desired file and also leaves pheromone to help subsequent search requests. Repantis and Kalogeraki

        [12] proposed a file sharing mechanism in which nodes use the Bloom filter to build content synopses of their data and adaptively disseminate them to other nodes to guide queries. Though the advertisement-based methods reduce the overhead of flooding-based methods, they still generate high overhead for advertising and cannot guarantee the success of file searching due to node mobility.

    2. P2P File Sharing in Disconnected MANETs

      The disconnected MANETs are featured by sparse node density and intermittent node connection, which makes previously introduced methods infeasible in such networks. We then further introduce two categories of P2P file sharing methods for disconnected MANETs.

      1. Cache/Replication-Based Methods

        Huang et al. [13] proposed a method that considers multiple factors (e.g., node mobility, file popularity, and file server topology) in creating file replicas in file servers to realize optimal file availability in content distribution community. Gao et al. [14] proposed cooperative caching in disruption tolerant networks. It replicas each file to network central locations, which are frequently visited by nodes in the system, to ensure efficient data access. QCR [15] uses file caching to realize effective multimedia content dissemination in opportunistic networks. In addition to node mobility and file popularity, it also considers the impatience of users when creating replicas. Lenders et al. [16] investigated wireless ad hoc podcasting, in which nodes store contents from their neighbors that are interested by themselves or the nodes they have met. Chen and Shen [17] deduced the optimal file replication strategy in MANETs by further considering nodes ability to meet nodes as a resource because replicas on these nodes can meet more requesters and, thus, have higher availability. Though these methods improve file availability,

        nodes in these methods passively wait for contents they are interested in rather than actively search files, which may lead to search delay.

      2. Social Network-Based Methods

As of late, informal organizations have been used in substance distributed/dispersal calculations [18], [19], [20],

[21] in deft systems. MOPS [18] gives substance based sub/pub benefit by using the long haul neighboring relationship between hubs. It aggregates hubs with incessant contacts and chooses hubs that interface diverse gatherings as representatives, which are in charge of intercommunity correspondence. At that point, substance and memberships are handed-off through intermediaries to reach diverse groups. Cleans just considers hub portability, while SPOON is more profitable by considering both hub investment and versatility as portrayed already. In addition, not at all like MOPS that just relies on upon the meeting of agents for intercommunity inquiry, SPOON upgrades the proficiency of intercommunity hunt by 1) allocating one representative for every known remote group, which serves to forward a question specifically to the destination group, and 2) using stable hubs (facilitator) to get messages from representatives.

3. THE DESIGN OF SPOON

In this section, we first present trace data analysis to verify the social network properties in a real MANET. A P2P MANET file sharing system usually consists of 1) a method to represent contents, 2) a node management structure, and 3) a file searching method based on steps 1 and 2. Accordingly, SPOON has three main components: 1) interest extraction, 2) structure construction including community structure and node role assignment, and 3) interest-oriented file searching and retrieval based on components 1 and 2.

We then present each component of SPOON.

    1. Trace Data Analysis

      To accept the relationship between hub investments and their contact frequencies, we examined the follow from the Haggle venture [26], which contains the experiencing records among

      98 cell phones conveyed by researchers going to the Infocom'06 meeting.

      TABLE 1: Average Number of Shared Interested Tracks .

      TABLE 2: Notations in Interest Extraction

      From the table, we see that for every group, hubs have higher normal number of imparted intrigued tracks to same group hubs than with hubs from different groups. Note that we utilized a generally detached group creation prerequisite that every hub just needs to have a high contact recurrence with 50% of hubs in a group. With a stricter prerequisite and a more advanced bunching system, hubs in the same group would impart more intrigued tracks. Above follows confirm the already watched social properties and backing the premise for SPOON that hubs with regular diversions have a tendency to meet oftentimes.

    2. Interest Extraction

      Without loss of generality, we assume that node contents can be classified to different interest categories. It was found that users usually have a few file categories that they query for files frequently in a file sharing system. Specifically, for the majority of users, 80 percent of their shared files fall into only 20 percent of total file categories [22]. Like other file sharing systems [27], [28], we consider that a nodes stored files can reflect its file interests. Thus, SPOON derives the interests of a node from its files. Table 2 lists the notations used in this section.

    3. Community Construction

      Interpersonal organization hypothesis uncovers that individuals with the same investment have a tendency to meet oftntimes [24]. By abusing this property, SPOON orders hubs with regular diversions and incessant contacts into a group to encourage investment based document seeking, as presented recent in Section 3.5. Hubs with different diversions fit in with various groups. The group development can undoubtedly be led in a unified way by gathering hub investments and contact frequencies from all hubs to a focal hub. Nonetheless, considering that the proposed framework is for conveyed detached MANETs, in which opportune data gathering and circulation is nontrivial, we further propose a decentralized strategy to guarantee the adaptivity of SPOON in genuine environment.

    4. Node Role Assignment

A past study has demonstrated that in an interpersonal organization comprising of versatile clients, just a some piece

of hubs have high degrees [20]. We can regularly discover a vital or prevalent individual who coordinates individuals in a group in our every day life. For instance, the school senior member directions distinctive divisions in the school and the division head unites with employees in the office. Consequently, we exploit diverse sorts of hub versatility for record offering.

We characterize group organizer and envoy hubs in the perspective of an interpersonal organization. A group facilitator is an imperative and prevalent hub in the group. It keeps lists of all documents in its group. Every group has one representative for every known outside group, which serves as the scaffold to the group. The organizer in a group keeps up the vC of remote groups and relating envoys to guide questions to representatives for intercommunity looking. The quantity of diplomats and facilitators can be balanced in view of the system size and workload to abstain from over- burdening these hubs. Since ministers and organizers assume more liability, we can likewise receive part revolution and additional motivations for reasonableness thought.

Because of page point of confinement, we leave this as our future work.

      1. Community Coordinator Node Selection

        We define a stable node that has tight contact frequency with other community members as the community coordinator. In network analysis, centrality is often used to determine the relative importance of a vertex within the network. We then adopt the improved degree centrality [32], which assigns weight to each link based on the contact frequency, for coordinator selection because it reflects the tightness of a node with other community members. In the initial phase of coordinator discovery.

      2. Community Ambassador Node Selection

An ambassador is used to bridge the coordinator in its home community and a foreign community. We use the product of a nodes contact frequency with its coordinator and that with the foreign community for ambassador selection.

    1. Interest-Oriented File Searching and Retrieval

      In informal communities, individuals more often than not have a couple record engages [22] and their document visit design by and large takes after a certain circulation [23]. Likewise, individuals with the same investment have a tendency to contact one another oftentimes [24]. Therefore, diversions can be a decent direction for record seeking. Considering the connection among hub development design [33], people's basic investments, and their contact

      frequencies, we can course record appeals to document holders in view of hubs' frequencies of meeting distinctive premiums.

      1. Intercommunity File Searching and Retrieval

        In the intercommunity looking calculation, a facilitator maps a solicitation to the outside group that is destined to contain the questioned document. Like the intercommunity hunt step, the organizer additionally utilizes the multicopy sending procedure. After getting the appeal, the facilitator in the outside group checks its record file to check whether its group has the document. If not, the organizer rehashes the intercommunity record looking by gazing upward its envoys to check for further sending open doors. In the event that the document exists, the facilitator requests the record from the record holder when meeting it and sends the record back to the requester's group through the relating minister. The organizer of the requester's group will further forward the document to the requester.

        Fig. 2 portrays the procedure of document looking, in which a requester (hub R) in group C1 creates a record demand. Since its neighbors inside number bounces don't have the document, the solicitation is then sent to the group organizer NC1. NC1 checks the group document lists yet can't discover the record.

        It then asks the group minister NA1 to forward the appeal to the remote group coordinating the questioned document. Utilizing the same route as NC1, the group organizer NC2 discovers the record and sends it back to the requester's group by means of diplomat NA2. The document is first sent to NC1, and after that sent to the requester. Calculation 2 demonstrates the pseudo code of the intercommunity looking calculation.

        1. CONCLUSION:

In this paper, we propose an informal community based P2P content record imparting framework in detached mobile Networks. SPOON considers both hub investment and contact recurrence for proficient document imparting. We present four primary segments of SPOON: Interest extraction distinguishes hubs' hobbies; Community development assembles normal investment hubs with incessant contacts into groups. The hub part task segment misuses hubs with tight association with group individuals for intra-community record looking and exceedingly portable hubs that visit outer groups every now and again for intercommunity document seeking; The investment arranged document scanning plan chooses sending hubs for questions in light of premium similitudes. SPOON likewise joins extra techniques for record prefetching, questioning consummation, and circle avoidance, and hub stir thought to further upgrade document seeking effectiveness

VIII. REFERENCE:

  1. The State of the Smartphone Market, http://www.allabout symbian.com/news/item/6671_The_State_of_the_Smartphone_ Ma.php, 2013.

  2. Next Generation Smartphones Players, Opportunities & Forecasts 2008-2013, technical report, Juniper Research, 2009.

  3. A Market Overview and Introduction to GyPSii, http:// corporate.gypsii.com/docs/MarketOverview, 2013.

  4. Bittorrent, http://www.bittorrent.com, 2013.

  5. Kazaa, http://www.kazaa.com, 2013.

  6. M. Papadopouli and H. Schulzrinne, A Performance Analysis of 7DS: A Peer-to-Peer Data Dissemination and Prefetching Tool for Mobile Users, Proc. IEEE Sarnoff Symp. Digest Advances in Wired and Wireless Comm., 2001.

  7. A. Klemm, C. Lindemann, and O. Waldhorst, A Special-Purpose Peer- to-Peer File Sharing System for Mobile Ad Hoc Networks, Proc. IEEE 58th Vehicular Technology Conf. (VTC 03), 2003.

  8. C. Lindemann and O.P. Waldhort, A Distributed Search Service for Peer-to-Peer File Sharing, Proc. Intl Conf. Peer-to-Peer Computing (P2P 02), 2002.

  9. D.W.A. Hayes, Peer-to-Peer Information Sharing in a Mobile Ad Hoc Environment, Proc. IEEE Sixth Workshop Mobile Computing Systems and Applications (WMCSA 04), 2004.

  10. J.B. Tchakarov and N.H. Vaidya, Efficient Content Location in Wireless Ad Hoc Networks, Proc. IEEE Intl Conf. Mobile Data Management (MDM 04), 2004.

  11. C. Hoh and R. Hwang, P2P File Sharing System over MANET based on Swarm Intelligence: A Cross-Layer Design, Proc. IEEE Wireless Comm. and Networking Conf. (WCNC 07), pp. 2674-2679, 2007.

  12. T. Repantis and V. Kalogeraki, Data Dissemination in Mobile Peer-to- Peer Networks, Proc. Sixth Intl Conf. Mobile Data Management (MDM 05), 2005.

  13. Y. Huang, Y. Gao, K. Nahrstedt, and W. He, Optimizing FileRetrieval in Delay-Tolerant Content Distribution Community, Proc. IEEE 29th Intl Conf. Distributed Computing Systems (ICDCS 09), 2009.

  14. W. Gao, G. Cao, A. Iyengar, and M. Srivatsa, Supporting Cooperative Caching in Disruption Tolerant Networks, Proc. 31st Intl Conf. Distributed Computing Systems (ICDCS 11), 2011.

  15. J. Reich and A. Chaintreau, The Age of Impatience: Optimal Replication Schemes for Opportunistic Networks, Proc. Fifth Intl Conf. Emerging Networking Experiments and Technologies (CoNEXT 09), 2009.

  16. V. Lenders, M. May, G. Karlsson, and C. Wacha, Wireless Ad Hoc Podcasting, ACM SIGMOBILE Mobile Computing and Comm. Rev., vol. 12, pp. 65-67, 2008.

  17. K. Chen and H. Shen, Global Optimization of File Availability through Replication for Efficient File Sharing in MANETs, Proc. IEEE 19th Intl Conf. Network Protocols (ICNP), 2011.

  18. F. Li and J. Wu, MOPS: Providing Content-Based Service in Disruption-Tolerant Networks, Proc. IEEE 29th Intl Conf.

  1. L. Kaufman and P. Rousseeuw, Finding Groups in Data: An Introduction to Cluster Analysis. John Wiley and Sons, 1990.

  2. E. Daly and M. Haahr, Social Network Analysis for Routing in Disconnected Delay-Tolerant MANETs, Proc. ACM MobiHoc,

2007.

Distributed Computing Systems (ICDCS 09), 2009.

[33]

W. Hsu, T. Spyropoulos, K. Psounis, and A. Helmy, Modeling Time-

[19]

P. Costa, C. Mascolo, M. Musolesi, and G.P. Picco, SociallyAware

Variant User Mobility in Wireless Mobile Networks, Proc. IEEE

Routing for Publish-Subscribe in Delay-Tolerant Mobile Ad Hoc Networks, IEEE J. Selected Areas in Comm., vol. 26, no. 5, pp. 748-

[34]

INFOCOM, 2007.

A. Vahdat and D. Becker, Epidemic Routing for PartiallyConnected

760, June 2008.

Ad Hoc Networks, technical report, Duke Univ., 2000.

[20]

E. Yoneki, P. Hui, S. Chan, and J. Crowcroft, A Socio-Aware Overlay

[35]

GENI Project, http://www.geni.net, 2013.

for Publish/Subscribe Communication in Delay Tolerant Networks,

[36]

Orbit, http://www.orbit-lab.org, 2013.

Proc. 10th ACM Symp. Modeling, Analysis, and Simulation of

[37]

The Network Simulator ns-2, http://www.isi.edu/nsnam/ns, 2013.

[21]

Wireless and Mobile Systems (MSWiM 07), 2007.

C. Boldrini, M. Conti, and A. Passarella, ContentPlace: SocialAware

[38]

M. Musolesi and C. Mascolo, Designing Mobility Models Based on Social Network Theory, ACM SIGMOBILE Computing and Comm.

Data Dissemination in Opportunistic Networks, Proc. 11th Intl Symp.

Rev., vol. 11, pp. 59-70, 2007.

Modeling, Analysis and Simulation Wireless and Mobile Systems (MSWiM 08), 2008.

[39]

N. Eagle, A. Pentland, and D. Lazer, Inferring Social Network Structure Using Mobile Phone Data, Proc. Natl Academy of Sciences

[22]

A. Fast, D. Jensen, and B.N. Levine, Creating Social Networks to

USA, vol. 106, no. 36, pp. 15274-15278, 2009.

Improve Peer-to-Peer Networking, Proc. 11th ACM SIGKDD Intl Conf. Knowledge Discovery in Data Mining (KDD 05), 2005.

[40]

K. Chen and H. Shen, Leveraging Social Networks for P2P Content- Based File Sharing in Mobile Ad Hoc Networks, Proc. IEEE Eighth

[23]

A. Iamnitchi, M. Ripeanu, and I.T. Foster, Small-World FileSharing

Intl Conf. Mobile Adhoc and Sensor Systems (MASS), 2011.

Communities, Proc. IEEE INFOCOM, 2004.

  1. M. Mcpherson, Birds of a Feather: Homophily in Social Networks, Ann. Rev. Sociology, vol. 27, no. 1, pp. 415-444 , 2001.

  2. E. Yoneki, P. Hui, S. Chan, and J. Crowcroft, A Socio-Aware Overlay for Publish/Subscribe Communication in Delay Tolerant Networks, Proc. 10th ACM Symp. Modeling, Analysis, and Simulation of Wireless and Mobile Systems (MSWiM 07), 2007.

  3. A. Chaintreau, P. Hui, J. Scott, R. Gass, J. Crowcroft, and C. Diot, Impact of Human Mobility on Opportunistic Forwarding Algorithms, IEEE Trans. Mobile Computing, vol. 6, no. 6, pp. 606-620, June 2007.

  4. V. Carchiolo, M. Malgeri, G. Mangioni, and V. Nicosia, An Adaptive Overlay Network Inspired by Social Behavior, J. Parallel and Distributed Computing, vol. 70, pp. 282-295, 2010.

  5. A. Iamnitchi, M. Ripeanu, E. Santos-Neto, and I. Foster, The Small World of File Sharing, IEEE Trans. Parallel and Distributed Systems, vol. 22, no. 7, pp. 1120-1134, July 2011.

  6. H. Schu¨tze and C. Silverstein, Projections for Efficient Document Clustering, Proc. 20th Ann. Intl ACM Conf. Research and Development in Information Retrieval (SIGIR 07), pp. 74-81, 1997.

  7. P. Bonacich, Factoring and Weighting Approaches to Status Scores and Clique Identification, J. Math. Sociology, vol. 2, pp. 113-120, 1972.

AUTHOR PROFILE

VijayaKumar C received BE degree in Computer Science Engineering from Visvesvaraya Technological University of Belgaum in 2013. Currently pursuing M.Tech degree in Visvesvaraya Technological University of Belgaum. His research interests include wireless sensor networks.

Shalini S received M.Tech degree in CNE from Visvesvaraya Technological University of Belgaum. She is currently working as Assistant professor in AMC Engineering College, Bangalore. Her areas of interests are wireless sensor networks.

Leave a Reply

Your email address will not be published. Required fields are marked *