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A mobile ad-hoc network is an autonomous system of mobile routers that are self-organizing and completely decentralized with no requirements for dedicated infrastructure support. However, such infrastructure in terms of base stations is available in many popular areas already. These base stations often offer high-speed data connectivity to a wired network. In this paper, we describe an approach where a combination of infrastructure and ad hoc communication can be used to better manage the data needs of a mobile wireless device. In our approach, base stations track user mobility and determine data usage patterns of users passing by. Based on this, future data needs of a mobile device can be predicted. Base stations can collaborate (over the wired network) to identify other mobile devices with spare capacity whose routes intersect that of a needy device and use these carriers to transport data. When such a carrier meets the needy device, they can form ad hoc per-to-peer communities to transfer the carried data. We also present the motivation, architecture and design of NUMI, our framework for supporting combined infrastructure and ad hoc peer-to-peer computing and prototype application built on top of this framework.

In this report, firstly, we presents state of the art survey on Data Management and Data Dissemination techniques with Mobile Sink. Moreover we classify these techniques into two ample sub-categories. Under this classification, we identify, review, compare, and highlight these techniques and their pros and cons. We do a SWOT (Strength, Weaknesses, Opportunities, Threats) analysis of each scheme. We also discuss where each scheme is appropriate. Secondly, we presents a new distributed data management scheme which is based upon Random Walk Based Membership Service to facilitate Data Dissemination in Mobile Sink based Wireless Sensor Networks. Our proposed scheme efficiently deals with the aforementioned problems and we also compare the characteristics of our proposed scheme with the state-of-the-art data-dissemination schemes. We propose using Random Walks (RWs) with uniformly distributed views to disseminate data through the WSN with a controlled overhead. This is performed by the use of a Random Walk Based Membership Service - the RaWMS. Our proposal solves then the problems generated when (a) all nodes are storage motes, being no aggregation performed (b) one center node plays the role of storage mote and aggregates data from all the other nodes (c) replication is performed on all nodes in the network. To the best of our knowledge, we are the first to propose an efficient data dissemination approach (in terms of overhead, adaptiveness and representativeness) to allow a mobile sink to gather a representative view of the monitored region covered by n sensor nodes by only visiting any m nodes, where hopefully m < < n.

In this report, firstly, we presents state of the art survey on Data Management and Data Dissemination techniques with Mobile Sink. Moreover we classify these techniques into two ample sub-categories. Under this classification, we identify, review, compare, and highlight these techniques and their pros and cons. We do a SWOT (Strength, Weaknesses, Opportunities, Threats) analysis of each scheme. We also discuss where each scheme is appropriate. Secondly, we presents a new distributed data management scheme which is based upon Random Walk Based Membership Service to facilitate Data Dissemination in Mobile Sink based Wireless Sensor Networks. Our proposed scheme efficiently deals with the aforementioned problems and we also compare the characteristics of our proposed scheme with the state-of-the-art data-dissemination schemes. We propose using Random Walks (RWs) with uniformly distributed views to disseminate data through the WSN with a controlled overhead. This is performed by the use of a Random Walk Based Membership Service - the RaWMS. Our proposal solves then the problems generated when (a) all nodes are storage motes, being no aggregation performed (b) one center node plays the role of storage mote and aggregates data from all the other nodes (c) replication is performed on all nodes in the network. To the best of our knowledge, we are the first to propose an efficient data dissemination approach (in terms of overhead, adaptiveness and representativeness) to allow a mobile sink to gather a representative view of the monitored region covered by n sensor nodes by only visiting any m nodes, where hopefully m < < n.

In this report, firstly, we presents state of the art survey on Data Management and Data Dissemination techniques with Mobile Sink. Moreover we classify these techniques into two ample sub-categories. Under this classification, we identify, review, compare, and highlight these techniques and their pros and cons. We do a SWOT (Strength, Weaknesses, Opportunities, Threats) analysis of each scheme. We also discuss where each scheme is appropriate. Secondly, we presents a new distributed data management scheme which is based upon Random Walk Based Membership Service to facilitate Data Dissemination in Mobile Sink based Wireless Sensor Networks. Our proposed scheme efficiently deals with the aforementioned problems and we also compare the characteristics of our proposed scheme with the state-of-the-art data-dissemination schemes. We propose using Random Walks (RWs) with uniformly distributed views to disseminate data through the WSN with a controlled overhead. This is performed by the use of a Random Walk Based Membership Service - the RaWMS. Our proposal solves then the problems generated when (a) all nodes are storage motes, being no aggregation performed (b) one center node plays the role of storage mote and aggregates data from all the other nodes (c) replication is performed on all nodes in the network. To the best of our knowledge, we are the first to propose an efficient data dissemination approach (in terms of overhead, adaptiveness and representativeness) to allow a mobile sink to gather a representative view of the monitored region covered by n sensor nodes by only visiting any m nodes, where hopefully m < < n.

In this report, firstly, we presents state of the art survey on Data Management and Data Dissemination techniques with Mobile Sink. Moreover we classify these techniques into two ample sub-categories. Under this classification, we identify, review, compare, and highlight these techniques and their pros and cons. We do a SWOT (Strength, Weaknesses, Opportunities, Threats) analysis of each scheme. We also discuss where each scheme is appropriate. Secondly, we presents a new distributed data management scheme which is based upon Random Walk Based Membership Service to facilitate Data Dissemination in Mobile Sink based Wireless Sensor Networks. Our proposed scheme efficiently deals with the aforementioned problems and we also compare the characteristics of our proposed scheme with the state-of-the-art data-dissemination schemes. We propose using Random Walks (RWs) with uniformly distributed views to disseminate data through the WSN with a controlled overhead. This is performed by the use of a Random Walk Based Membership Service - the RaWMS. Our proposal solves then the problems generated when (a) all nodes are storage motes, being no aggregation performed (b) one center node plays the role of storage mote and aggregates data from all the other nodes (c) replication is performed on all nodes in the network. To the best of our knowledge, we are the first to propose an efficient data dissemination approach (in terms of overhead, adaptiveness and representativeness) to allow a mobile sink to gather a representative view of the monitored region covered by n sensor nodes by only visiting any m nodes, where hopefully m < < n.

In this report, firstly, we presents state of the art survey on Data Management and Data Dissemination techniques with Mobile Sink. Moreover we classify these techniques into two ample sub-categories. Under this classification, we identify, review, compare, and highlight these techniques and their pros and cons. We do a SWOT (Strength, Weaknesses, Opportunities, Threats) analysis of each scheme. We also discuss where each scheme is appropriate. Secondly, we presents a new distributed data management scheme which is based upon Random Walk Based Membership Service to facilitate Data Dissemination in Mobile Sink based Wireless Sensor Networks. Our proposed scheme efficiently deals with the aforementioned problems and we also compare the characteristics of our proposed scheme with the state-of-the-art data-dissemination schemes. We propose using Random Walks (RWs) with uniformly distributed views to disseminate data through the WSN with a controlled overhead. This is performed by the use of a Random Walk Based Membership Service - the RaWMS. Our proposal solves then the problems generated when (a) all nodes are storage motes, being no aggregation performed (b) one center node plays the role of storage mote and aggregates data from all the other nodes (c) replication is performed on all nodes in the network. To the best of our knowledge, we are the first to propose an efficient data dissemination approach (in terms of overhead, adaptiveness and representativeness) to allow a mobile sink to gather a representative view of the monitored region covered by n sensor nodes by only visiting any m nodes, where hopefully m < < n.

In this report, firstly, we presents state of the art survey on Data Management and Data Dissemination techniques with Mobile Sink. Moreover we classify these techniques into two ample sub-categories. Under this classification, we identify, review, compare, and highlight these techniques and their pros and cons. We do a SWOT (Strength, Weaknesses, Opportunities, Threats) analysis of each scheme. We also discuss where each scheme is appropriate. Secondly, we presents a new distributed data management scheme which is based upon Random Walk Based Membership Service to facilitate Data Dissemination in Mobile Sink based Wireless Sensor Networks. Our proposed scheme efficiently deals with the aforementioned problems and we also compare the characteristics of our proposed scheme with the state-of-the-art data-dissemination schemes. We propose using Random Walks (RWs) with uniformly distributed views to disseminate data through the WSN with a controlled overhead. This is performed by the use of a Random Walk Based Membership Service - the RaWMS. Our proposal solves then the problems generated when (a) all nodes are storage motes, being no aggregation performed (b) one center node plays the role of storage mote and aggregates data from all the other nodes (c) replication is performed on all nodes in the network. To the best of our knowledge, we are the first to propose an efficient data dissemination approach (in terms of overhead, adaptiveness and representativeness) to allow a mobile sink to gather a representative view of the monitored region covered by n sensor nodes by only visiting any m nodes, where hopefully m < < n.

In this report, firstly, we presents state of the art survey on Data Management and Data Dissemination techniques with Mobile Sink. Moreover we classify these techniques into two ample sub-categories. Under this classification, we identify, review, compare, and highlight these techniques and their pros and cons. We do a SWOT (Strength, Weaknesses, Opportunities, Threats) analysis of each scheme. We also discuss where each scheme is appropriate. Secondly, we presents a new distributed data management scheme which is based upon Random Walk Based Membership Service to facilitate Data Dissemination in Mobile Sink based Wireless Sensor Networks. Our proposed scheme efficiently deals with the aforementioned problems and we also compare the characteristics of our proposed scheme with the state-of-the-art data-dissemination schemes. We propose using Random Walks (RWs) with uniformly distributed views to disseminate data through the WSN with a controlled overhead. This is performed by the use of a Random Walk Based Membership Service - the RaWMS. Our proposal solves then the problems generated when (a) all nodes are storage motes, being no aggregation performed (b) one center node plays the role of storage mote and aggregates data from all the other nodes (c) replication is performed on all nodes in the network. To the best of our knowledge, we are the first to propose an efficient data dissemination approach (in terms of overhead, adaptiveness and representativeness) to allow a mobile sink to gather a representative view of the monitored region covered by n sensor nodes by only visiting any m nodes, where hopefully m < < n.