Multipath TCP (MPTCP) recently emerges as a promising tool to improve the network service to vehicles through transparent aggregation of wireless infrastructures on the Earth (e.g., current terrestrial BSs) and over the air [e.g., unmanned aerial vehicles (UAVs)-based BSs], e.g., using both LTE and WiFi at the same time for a data transfer. Currently, such an approach is challenged by the fast dynamism of wireless link characteristics (e.g., RTT and loss rate) during the handoff between wireless access points under vehicle mobility, which could easily cause Head-of-Line (HoL) blocking at the receiver and significantly lower the overall network performance. The existing solutions generally rely on asynchronous scheduling at the sender to tackle the HoL blocking. However, they fall short in handling the packet losses and excessive delay during the handoff. In this article, we propose a unique MPTCP scheduling scheme named efficient bandwidth aggregation (EBA) to tackle the drawback in current approaches. EBA adaptively enables packet duplication over parallel paths (i.e., redundant scheduling), which can effectively prevent the HoL blocking but losses some bandwidth. Thus, we carefully model the conditions under which packet duplication can improve network performance. We then dynamically turn on and off redundant scheduling based on the modeling to achieve the best bandwidth performance for vehicles. We have implemented EBA inside the current Linux kernel MPTCP and tested it extensively through simulated scenarios. Experimental results show that EBA can effectively enhance the network service for connected vehicles.

Named data networking (NDN) recently arises as a promising networking paradigm to support the Internet of Things (IoT) due to its data-centric architecture. However, NDN integrates application-layer semantics into the packet forwarding plane, which presents new attack faces. In this article, we aim to handle two attacks that exploit such vulnerabilities, namely the blackhole attack and the content poisoning attack. The two attacks are not handled efficiently by existing approaches due to the challenge in minimizing routers that need to be detoured to isolate attackers. Therefore, in this article, we propose a novel method named SmartDetour to tackle the challenge in a distributed manner. SmartDetour contains two components: 1) a proactive reputation updating algorithm and 2) a reputation-based probabilistic forwarding strategy. The former updates the reputation of forwarding candidates based on whether they must be detoured upon packet failures. The latter selects the next-hop router for interest packets probabilistically based on the reputations of forwarding candidates. The two components work together to isolate attackers with minimal detouring needed. Extensive ndnSIM-based simulation shows that SmartDetour can effectively identify and isolate attackers.

So far, there is no file replication method that tries to reduce data loss in correlated node failures, which however are common in Disruption Tolerant Networks (DTNs). In this paper, we propose a distributed file replication method (called MobileCopy) in DTNs, which aims to achieve low probability of totally losing a file at the expense of having a high number of impacted files in an individual large-scale correlated node failure. MobileCopy is designed for community-based file sharing systems. It has two main components: i) data loss resistant and popularity aware file replication, and ii) distributed hash table (DHT)-based file replica indexing. MobileCopy considers file popularity to determine the number of replicas of a file in each community. Through limiting the possible combination of candidate replica holders, MobileCopy greatly reduces the probability of node failures that will lead to data loss, i.e., losing all replicas of a file. Moreover, MobileCopy enables nodes to efficiently store and fetch the placement information of file replicas through competition based file replication and considering node mobility throughput among communities. Extensive trace-driven experiments demonstrate the effectiveness of MobileCopy against correlated node failures compared with previous methods.

Multipath TCP (MPTCP) enables a client to exploit multiple wireless paths simultaneously for improved throughput and mobility resilience. However, MPTCP clients in WiFi networks may easily lower the achievable throughput of the network due to excessively created connections over access points (APs), particularly those that own a weak link quality. This is caused by the fact that the maximal achievable throughput of a WiFi AP can be easily affected by the number of connections accessing it and the link qualities of those connections. In this paper, we first verify such effects through extensive experiments and analysis. We then propose a novel scheme, denoted MPWiFi, to solve this issue while keeping the benefits of MPTCP based multipath access in WiFi networks. Our scheme allows a MPTCP client to obtain resources on its best WiFi path freely and suppresses its subflows in additional paths when congestion happens. As a result, the degrading to the WiFi AP's achievable throughput is greatly prevented with acceptable influences on the benefits of MPTCP clients (i.e., their multipath access is intervened only on congested non-best APs). The fairness to MPTCP clients is also guaranteed through their best WiFi connection. The proposed solution is implemented along with the Linux Kernel MPTCP implementation. Extensive real-world deployment based experiments and NS3 simulation show that the proposed scheme can effectively alleviate the adverse impact of MPTCP based multipath access in WiFi networks while keeping its benefits.

Connected vehicle (CV) has emerged as a new computing and networking paradigm recently that can enable many beneficial CV applications. In this paper, we argue that Named Data Networking (NDN) presents a good synergy with the needs of CV applications. This drives us to propose an NDN based CV application framework with a distributed data service model. However, the fast mobility and vast moving area of vehicles lead to significant challenges on the efficiency and scalability of the underlying NDN backbone in the framework. To handle this issue, we propose a novel hierarchical hyperbolic NDN architecture (H2NDN). By taking advantage of the location dependency of CV applications, we design a hierarchical router topology and the associated namespace. This enables Interest packets from CV applications to be forwarded towards Data (cache) holders efficiently through static FIB configuration. However, the resultant hierarchical routing can easily overload high-level routers. Thus, we further integrate hyperbolic routing into the architecture through carefully designed hyperbolic planes in the hierarchical topology. As a result, the load is better balanced to ensure the overall scalability. Finally, extensive NDNsim based simulation with real traffic data proves the efficiency and scalability of the proposed H2NDN architecture.

A mobile ad hoc network (MANET) is an infrastructure-free network where mobile devices are connected wirelessly and can move in arbitrary directions. Mobile ad hoc networks can be utilized in many applications, ranging from sensor networks, autonomous vehicles, battlefield communication, to disaster rescue operations, etc. However, existing TCP/IP based Internet architecture that supports MANET has many limitations, such as dependency on end-to-end IP address-based communication and out-of-band security mechanisms, to enable it to work in an efficient and secured manner. The emerging Named Data Networking (NDN) architecture can help address many such problems fundamentally. NDN is a new information centric network architecture that features name-based data, in-network caching, and built-in security. To test and verify the features of this new paradigm, in this paper, we set up several real and low-interference mobile ad hoc environments using Raspberry Pi-based mini cars and built NDN applications on top of the infrastructure. We examined the performance of the NDN applications with various network settings in both static and mobile modes and demonstrated the effectiveness of NDN architecture in terms of in-network caching and information centric features.

Resource allocation optimization is critical to the overall performance of wireless heterogeneous networks (HetNet). Endpoint flow association optimization tries to reach a target resource allocation outcome by only controlling the associations of data flows to abstract/concrete network interfaces at the two ends of communication sessions. An instance of this problem in a single cellular heterogeneous network is the user association optimization problem, which plans the usage of macrocells and picocells. In this paper, we focus on this problem in a multi-provider HetNet, where the component wireless networks belong to different organizations. We identify and abstract the problem, comparing with the similar systems that are under the control of a single provider. After analyzing the changes in the new context and their implications, we provide a general centralized over-the-top network service design, which does not assume controls to the underlying network infrastructure. With the problem and design in mind, we then explore the performance problem when extending the existing user association schemes in a single-provider context to the new design. Though various association schemes are proposed in the prior research under different contexts, few of them provide an in-depth evaluation to several fundamental problems that are required by the problem in single/multi-provider context, i.e. 1) the distances of the association schemes to the optimal solution under various scenarios; 2) the sources and impacts of the potential throughput estimation errors. By using relatively small scale and more controlled scenarios, this paper is the first to provide answers to the above questions, which are valuable for guiding further studies and real system designs.

Due to the explosive growth of data demand from mobile devices, cellular operators have been exploring the use of WiFi to offload traffic from the LTE network. Such an integration opens the door for exploiting the network usage diversity for further overall network performance improvement, by intelligently and dynamically scheduling flows over the most appropriate network. However, how such a function can be efficiently and systematically realize, is missing from the current standard specifications, especially on the network infrastructure side. In this paper, we aim to solve such a challenge by proposing a Software-Defined Networking (SDN) based flow scheduling system that is compatible to the 3GPP LTE-WiFi integration framework. The global view provided by SDN makes it easy to collect necessary flow information, and the flexible control of SDN enables efficient flow scheduling. We view the flow scheduling problem as an overall network utility maximization problem. We prove its hardness and propose an approximation algorithm for solving the problem. The proposed system can be incrementally deployed over existing wireless network infrastructure. With extensive simulations in NS3 and demo implementation, we prove the feasibility and effectiveness of both the framework and the scheduling algorithm.

Correlating the congestion control (CC) of parallel subflows of multipath TCP (MPTCP) has shown the advantage of making it fair and friendly to legacy TCP. But the correlation also leads to some new drawbacks. In this paper, we first analyze major correlated MPTCP CC algorithms through the perspective of bandwidth competition. Based on the modeling, we verify, discover, and explain three shortages of correlated CC, namely 1) limit fairness semantic; 2) render new attack surfaces; and 3) interplay with network sharing policies. We further find that decoupling the CC of subflows is more promising in solving the above issues. However, directly applying legacy TCP CC to each subflow independently would lose the benefits of correlated CC. This motivates the design of an algorithm that decouples the CC of subflows as much as possible while still making MPTCP fair and friendly. To attain this goal, we translate the goals of correlated CC into an approximation principle under the decoupled semantic. We then propose a self-Constrained And Decoupled Increase Algorithm (CADIA) that achieves the principle by adaptively detecting and constraining non-best subflows. This makes CADIA share the benefits of correlated CC algorithms, while owning no direct correlation among the CC of subflows. Extensive analysis and experiments are conducted to demonstrate the effectiveness of CADIA.

The emergence of multipath TCP (MPTCP) has made it much easier for mobile devices to use multiple wireless network access paths simultaneously. However, we find that a large amount of multipath users could negatively impact the performance of wireless networks in terms of throughput and fairness due to increased amount of wireless connections. Therefore, in this paper, we aim to mitigate such a problem while retaining the benefits of multipath access in wireless networks from the perspective of network owner. We solve the challenge by 1) identifying a solution principle that can effectively balance the two goals and 2) implementing the principle through an SDN based bandwidth usage management system on the network side. When there is congestion on an AP, our method enforces necessary suppressions on non-primary subflows from multipath users to protect the network performance, while keeping the multipath benefits as much as possible. When an AP owns idled capacity, no intervention is imposed, thus offering the maximal benefits to multipath users without substantially affecting the network performance. Thus, the multipath access is dynamically scaled to achieve a balance of the two goals. Extensive NS3 experiment with Linux Kernel MPTCP implementation demonstrates our findings as well as the effectiveness of the proposed system.

Present approaches to achieve k-coverage for Wireless Sensor Networks still rely on centralized techniques. In this paper, we devise a distributed method for this problem, namely Distributed VOronoi based Cooperation scheme (DVOC), where nodes cooperate in hole detection and recovery. In previous Voronoi based schemes, each node only monitors its own critical points. Such methods are inefficient for k-coverage because the critical points are far away from their generating nodes in k-order Voronoi diagram, causing high cost for transmission and computing. As a solution, DVOC enables nodes to monitor others' critical points around themselves by building local Voronoi diagrams (LVDs). Further, DVOC constrains the movement of every node to avoid generating new holes. If a node cannot reach its destination due to the constraint, its hole healing responsibility will fall to other cooperating nodes. The experimental results from the real world testbed demonstrate that DVOC outperforms the previous schemes.

Datacenters should provide bandwidth guarantees to tenants for performance predictability. Ideally, this process should attain three important characteristics: work conservation, fairness, and simplicity. The first one indicates that tenants can utilize unused bandwidths effectively without harming the bandwidth guarantee. The second one means that tenants share the unused bandwidth following a certain fairness policy. The last one requires that the developed scheme can be easily deployed with commodity software and hardware. However, achieving all requirements at the same time is challenging considering the distributed nature of bandwidth usage in datacenters. In this paper, we present our practical approach that can solve the aforementioned challenges using multipath TCP (MPTCP). With MPTCP, we split each TCP flow into one bandwidth guarantee (BG) subflow and one work conservation (WC) subflow. We treat all BG subflows and UDP flows as BG traffic and WC subflows as WC traffic. We let BG traffic go through a high priority queue on switches to guarantee allocated bandwidth. WC traffic goes through a low priority queue to grab unused bandwidths without harming bandwidth guarantee. We tune the aggressiveness of WC subflows to achieve the fairness policy. The overall scheme can be easily deployed on commodity servers and switches. We implement our approach along with the Linux kernel MPTCP implementation. Extensive testbed experiments show that our scheme achieves all the three goals with design simplicity compared to prior work.

We found that directly employing MPTCP in WiFi network might adversely affect the overall network performance. The connecting MPTCP client achieves little bandwidth advantage through redundant paths of weak signal strength. However, it impairs the overall network performance by unintentionally reducing the throughput available to other clients sharing that access point in much greater extent. In this paper, we analyzed this phenomenon and provided a method, which improves the adverse impact of MPTCP significantly.

In state-of-the-art Delay Tolerant Network (DTN) routing algorithms, two encountering nodes rely on routing utilities (e.g., probabilities of meeting other nodes) to decide the better carrier (defined forwarder) for their packets. As the utilities and forwarder information reflect user privacy, nodes may be reluctant to disclose such information, which however is indispensable in routing. To handle this challenge, we propose two distributed strategies to protect the aforementioned private information in utility-based DTN routing algorithms while still guarantying the correctness of packet forwarding, namely meeting Relationship Anonymity (ReHider) and Forwarder Anonymity (FwHider). ReHider anonymizes routing utilities between two encountered nodes, while FwHider additionally hides the forwarder information among the group of encountered nodes on top of the routing utility anonymity. We also present enhanced versions of the two strategies that can better prevent certain malicious behaviors such as probing attack and brute-force attack. The proposed strategies are distributed without the need of a central authority for authentication or key management. They can be applied to any utility-based DTN routing algorithms. Extensive analysis, trace-driven simulation, and smartphone based test demonstrate the effectiveness and energy efficiency of the proposed strategies.

In mobile opportunistic social networks (MOSNs), mobile devices carried by people communicate with each other directly when they meet for proximity-based MOSN services (e.g., file sharing) without the support of infrastructures. In current methods, when nodes meet, they simply communicate with their real IDs, which leads to privacy and security concerns. Anonymizing real IDs among neighbor nodes solves such concerns. However, this prevents nodes from collecting real ID-based encountering information, which is needed to support MOSN services. Therefore, in this paper, we propose FaceChange that can support both anonymizing real IDs among neighbor nodes and collecting real ID-based encountering information. For node anonymity, two encountering nodes communicate anonymously. Only when the two nodes disconnect with each other, each node forwards an encrypted encountering evidence to the encountered node to enable encountering information collection. A set of novel schemes are designed to ensure the confidentiality and uniqueness of encountering evidences. FaceChange also supports fine-grained control over what information is shared with the encountered node based on attribute similarity (i.e., trust), which is calculated without disclosing attributes. Advanced extensions for sharing real IDs between mutually trusted nodes and more efficient encountering evidence collection are also proposed. Extensive analysis and experiments show the effectiveness of FaceChange on protecting node privacy and meanwhile supporting the encountering information collection in MOSNs. Implementation on smartphones also demonstrates its energy efficiency.

In this paper, we introduce RoadAware, an infrastructure-less system that leverages a smartphone to collect road information on people's daily routes to and from work. Unlike previous research that utilizes moving vehicles equipped with sensors to collect road information, RoadAware does not need the support from infrastructure, road-side facilities or other users and focuses on serving individuals during his/her daily commute to and back from work. RoadAware can provide road information including 1) travel distance and time between traffic lights; 2) duration of red and green signals of each traffic light; and 3) traffic volume on the road between traffic lights. RoadAware builds a model that can deduce the road information based on the wait time and the length of the waiting queue in front of the car when it stops at a traffic light. The road information not only benefits individuals in their daily commutes (e.g., predict waiting at red lights and remind whether there is a delay on daily route) but can also be collected for traffic optimization that otherwise requires costly sensor deployment. We developed RoadAware on Windows smartphones, and our extensive real-world test shows that RoadAware can provide road information with acceptable accuracy.

We consider learning the underlying graph structure of a network in which infection spreads based on the observations of node infection times. We give an algorithm based on minimal hitting set to learn the exact underlying graph structure and provide sufficient condition on number of cascades required (i.e. sample complexity) for reliable recovery, which is shown to be O(logn), where n is the number of nodes in the graph. We then analytically evaluate performance of minimal hitting set approach in learning the degree distribution and detecting leaf nodes of a graph and provide a sufficient condition for its sample complexity which is shown to be lower than that of learning the whole graph. We also generalize the exact graph estimation problem to the problem of estimating the graph within a certain distortion, measured by edit distance. We show that this edit distance based graph estimator has a lower sample complexity. Our experimental results based on both synthetic network topologies and a real-world network trace show that our algorithm achieves superior performance than a previously proposed algorithm based on maximum likelihood.

Nodes in Delay Tolerant Networks (DTN) rely on routing utilities (e.g., probabilities of meeting nodes) to decide the packet forwarder. As the utilities reflect user privacy, nodes may be reluctant to disclose such information directly. Therefore, we propose a distributed strategy to protect the aforementioned private information in utility-based DTN routing algorithms while still guarantying the correctness of packet forwarding, namely meeting Relationship Anonymity (ReHider). We also present an enhanced version that can better prevent certain malicious behaviors (probing attack and brute-force attack). Initial analysis show the effectiveness of the proposed strategy.

The explosive growth of personal mobile devices (e.g., smartphones and pads) has brought about significant potential distributed sensing resources. However, such resources have not been fully utilized due to two problems: i) mobile device mobility usually is not dedicated to data sensing, and ii) users may not be willing to participate in the data sensing proactively, i.e., move to or wait in a specific area. To address these problems, we propose a sensing system, namely MobiSensing, with a low intervention to device owners. It uses the semi-Markov process to model node mobility for future mobility prediction. While moving around, mobile devices connect to the central task assignment server opportunistically through their owners' daily usage. In each connection, the server predicts the connected device's next connection and its mobility between current and the next connection. Then, the server assigns sensing tasks in this period of time that the node is likely to complete to the node. As a result, no proactive operations or movements are required for device owners, and sensing tasks can be completed passively and efficiently. Trace-driven experiments demonstrate the high successful rate of MobiSensing.

Mobile devices nowadays can find multiple wireless networks, such as WiFi, 4G/LTE and relay through devices. These networks have different characteristics in terms of coverage, data rate, and price. Meanwhile, mobile applications (and even different TCP/UDP connections) often have diverse and time-variant network needs. Thus, to better use all wireless network resources, it would be ideal to enable a TCP/UDP connection to 1) select the most appropriate network dynamically and 2) migrate between networks transparently. However, existing methods fail to provide both functions in a systematic and efficient way at the TCP/UDP connection level. In this paper, we adopt Software-Defined Networking (SDN) to realize such a feature. We use the features of SDN to realize intelligent network selection that is adaptive to time-variant application needs, network availability, and scheduling commands. To support transparent migration, an intelligent home agent (HA) is designed with the SDN to anchor packets from the mobile device. It can intelligently determine which wireless network a TCP/UDP connection is running over. Finally, our implementation demonstrates the effectiveness and efficiency of the proposed system.

In delay tolerant networks (DTNs), enabling a mobile node to search and find another interested mobile node is an important function in many applications. However, the movement of nodes in DTNs makes the problem formidable. Current node searching methods in disconnected networks mainly rely on fixed stations in the network and infrastructure-based communication to collect node position information, which is difficult to implement in DTNs. In this paper, we present DSearching, a distributed mobile node searching scheme for DTNs that requires no infrastructure. In DSearching, the entire DTN area is split into sub-areas, and each node summarizes its mobility information as both transient sub-area visiting record and long-term movement pattern. Upon arriving at a sub-area, a node generates a new visiting record for the sub-area and distributes it to nodes that are likely to stay in the previous sub-area, so that visiting records form a chain for the locators to trace the node. Each node also stores different parts of its long-term mobility pattern to long-staying nodes in different sub-areas for others to trace it when visiting records are absent. Considering that nodes in DTNs usually have limited resources, DSearching constrains the communication and storage cost in the information distribution while enabling efficient node searching. Advanced extensions that can further improve the searching efficiency is also proposed in this paper. Extensive trace-driven experiments with real traces demonstrate the high efficiency and high effectiveness of DSearching.

Node searching in delay tolerant networks is of great importance for different applications, in which a locator node finds a target node in person. In the previous distributed node searching method, a locator traces the target along its movement path from its most frequently visited location. For this purpose, nodes leave traces during their movements and also store their long-term movement patterns in their frequently visited locations (i.e., preferred locations). However, such tracing leads to a long delay and high overhead on the locator by long-distance moving. Our trace data study confirms these problems and provides the foundation of our design of a new node searching method, called target-oriented method (TSearch). By leveraging social network properties, TSearch aims to enable a locator to directly move toward the target. Nodes create encounter records (ERs) indicating the locations and times of their encounters and make the ERs easily accessible by locators through message exchanges or a hierarchical structure. In node searching, a locator follows the target's latest ER, the latest ERs of its friends (i.e., frequently meeting nodes), its preferred locations, and the target's possible locations deduced from additional information for node searching. Extensive trace-driven and real-world experiments show that TSearch achieves significantly higher success rate and lower delay in node searching compared with previous methods.

Distributed file searching in delay tolerant networks formed by mobile devices can potentially support various useful applications. In such networks, nodes often present certain social network properties of their holders in terms of contents (i.e., interests) and contacts. However, current methods in DTNs only consider either content or contact for file searching or dissemination, which limits the file sharing efficiency. In this paper, we first analyze real traces to confirm the importance and necessity of considering both content and contact in file search. We then propose Cont2, a social-aware file search method that exploits both node contents and contact patterns. First, considering people with common interests tend to share files and gather together, Cont2virtually groups common-interest nodes into a community to direct file search. Second, considering human mobility follows a certain pattern, Cont2exploits nodes' contact frequencies with a community to expedite file searching. To further improve the searching efficiency, Cont2also integrates sub-communities and parallel forwarding as optional components for file searching. Trace-driven experiments on the GENI testbed and NS-2 simulator show that Cont2can effectively improve the search efficiency compared to current methods.

In Vehicle Delay Tolerant Networks (VDTNs), current routing algorithms select relay vehicles based on either vehicle encounter history or predicted future locations. The former method may fail to find relays that can encounter the target vehicle in a large-scale VDTN while the latter method may not provide accurate location prediction due to traffic variance. Therefore, these methods cannot achieve high performance in terms of routing success rate and delay. In this paper, we aim to improve the routing performance in VDTNs. We first analyze vehicle network traces and observe that i) each vehicle has only a few active sub-areas that it frequently visits, and ii) two frequently encountered vehicles usually encounter each other in their active sub-areas. We then propose Active Area based Routing method (AAR) which consists of two steps based on the two observations correspondingly. AAR first distributes a packet copy to each active sub-area of the target vehicle using a traffic-considered shortest path spreading algorithm, and then in each sub-area, each packet carrier tries to forward the packet to a vehicle that has high encounter frequency with the target vehicle. Extensive trace-driven simulation demonstrates that AAR produces higher success rates and shorter delay in comparison with the state-of-the-art routing algorithms in VDTNs.

In mobile opportunistic social networks (MOSNs), mobile devices carried by people communicate with each other directly when they meet for proximity-based MOSN services (e.g., file sharing) without the support of infrastructures. In current methods, when nodes meet, they simply communicate with their real IDs, which leads to privacy and security concerns. Anonymizing real IDs among encountering neighbor nodes solves such concerns. However, this prevents nodes from collecting real ID based encountering information, which is needed to support MOSN services. Therefore, in this paper, we propose FaceChange that can support both anonymizing real IDs among neighbor nodes and collecting real ID based encountering information. To realize neighbor node anonymity, two encountering nodes communicate anonymously. Then, when the two nodes disconnect, each node forwards an encrypted encountering evidence to the encountered node to enable encountering information collection. A set of novel schemes are designed to protect the confidentiality and uniqueness of encountering evidences. FaceChange also supports fine-grained control over what encountering information should be forwarded based on attribute similarity (i.e., trust) without disclosing attributes. Extensive analysis and experiments show the effectiveness of FaceChange on protecting node privacy and meanwhile supporting the encountering information collection in MOSNs. Real implementation on smartphones also demonstrates its energy efficiency.

Node searching in delay tolerant networks (DTNs) is of great importance for different applications, in which a locator node finds a target node in person. In the previous distributed node searching method, a locator traces the target along its movement path from its most frequently visited location. For this purpose, nodes leave traces during their movements and also store their long-term movement patterns in their frequently visited locations (i.e., preferred locations). However, such tracing leads to a long delay and high overhead on the locator by longdistance moving. Our trace data study confirms these problems and provides foundation of our design of a new node searching method, called target-oriented method (TSearch). By leveraging social network properties, TSearch aims to enable a locator to directly move towards the target. Nodes create encounter records (ERs) indicating the locations and times of their encounters and make the ERs easily accessible by locators through message exchanges or a hierarchical structure. In node searching, a locator follows the target's latest ER, the latest ERs of its friends (i.e., frequently meeting nodes), and its preferred locations in order. Extensive trace-driven and real-world experiments show that TSearch achieves significantly higher success rate and lower delay in node searching compared with previous methods.

Delay Tolerant Networks (DTNs) have attracted significant interests due to the adaptability in areas without infrastructures. In such scenarios, moving data from one place (landmark) to another place (landmark) is essential for data communication between different areas. However, current DTN routing algorithms either fail to fully utilize node mobility or have additional requirements that cannot be satisfied easily (i.e., Require base stations or the global traffic distribution). Therefore, in this paper, we propose a distributed greedy routing algorithm, namely Greedy Flow, for efficient packet routing between landmarks. Greedy Flow builds a local traffic map and a global landmark map on each node. The local traffic map indicates the node's knowledge about the amount of traffic (node transition) between landmarks in the area where it primarily visits. It is constructed by collecting encountered nodes' transit frequencies between these landmarks. The global landmark map shows the distribution of landmarks in the system and is built offline. In packet routing, the global landmark map shows the general packet forwarding direction, while the local traffic map helps determine the next-hop landmark on the fastest path in the forwarding direction. As a result, packets are greedily forwarded toward their destination landmarks. Extensive real trace driven experiments demonstrate the high efficiency of Greedy Flow.

Present approaches to achieve k-coverage for Wireless Sensor Networks still rely on centralized techniques. In this paper, we devise a distributed method for this problem, namely Distributed VOronoi based Cooperation scheme (DVOC), where nodes cooperate in hole detection and recovery. In previous Voronoi based schemes, each node only monitors its own critical points. Such methods are inefficient for k-coverage because the critical points are far away from their generating nodes in k-order Voronoi diagram, causing high cost for transmission and computing. As a solution, DVOC enables nodes to monitor others' critical points around themselves by building local Voronoi diagrams (LVDs). Further, DVOC constrains the movement of every node to avoid generating new holes. If a node cannot reach its destination due to the constraint, its hole healing responsibility will fall to other cooperating nodes. The experimental results from the real world testbed demonstrate that DVOC outperforms the previous schemes.

Current reputation systems for peer-to-peer (P2P) file sharing systems either fail to utilize existing trust within social networks or suffer from certain attacks (e.g., free-riding and collusion). To handle these problems, we introduce a trust management system, called SocialLink, that utilizes social network and historical transaction links. SocialLink manages file transactions through both the social network and a novel weighted transaction network, which is built based on previous file transaction history. First, SocialLink exploits the trust among friends in social networks by enabling two friends to share files directly. Second, the weighted transaction network is utilized to 1) deduce the trust of the client on a server in reliably providing the requested file and 2) check the fairness of the transaction. In this way, SocialLink prevents potential misbehaving transactions (i.e., providing faulty files), encourages nodes to contribute file resources to non-friends, and avoids free-riding. Furthermore, the weighted transaction network helps SocialLink resist whitewashing, collusion and Sybil attacks. Extensive simulation demonstrates that SocialLink can efficiently ensure trustable and fair P2P file sharing and resist the aforementioned attacks.

Motivated by the growing popularity of mobile devices and their increasing capacities, file sharing in disruption tolerant networks (DTNs) has attracted significant attention recently. Since nodes are sparsely distributed in separated areas and are intermittently disconnected in DTNs, it is difficult to achieve high data availability in file sharing. Many previous methods enhance file availability in DTNs through file replication. However, there has been no file replication method that tries to reduce data loss in correlated node failures, which however are common in wireless networks. In this paper, we propose a distributed file replication method (called MobileCopy) in DTNs, which aims to achieve low probability of totally losing a file at the expense of having a high number of impacted files in an individual large-scale correlated node failure. MobileCopy is designed for community-based file sharing systems. It has two main components: i) data loss resistant and popularity aware file replication, and ii) distributed hash table (DHT)-based file replica indexing. MobileCopy considers file popularity to determine the number of replicas of a file in each community. Through limiting the possible combination of candidate replica holders, MobileCopy greatly reduces the probability of node failures that will lead to data loss, i.e., losing all replicas of a file. Moreover, MobileCopy enables nodes to efficiently store and fetch the placement information of file replicas for efficient file searching. Extensive trace-driven experiments show that MobileCopy is robust against correlated node failures and efficient in file sharing in comparison with previous methods.

File sharing applications in mobile ad hoc networks (MANETs) have attracted more and more attention in recent years. The efficiency of file querying suffers from the distinctive properties of such networks including node mobility and limited communication range and resource. An intuitive method to alleviate this problem is to create file replicas in the network. However, despite the efforts on file replication, no research has focused on the global optimal replica creation with minimum average querying delay. Specifically, current file replication protocols in mobile ad hoc networks have two shortcomings. First, they lack a rule to allocate limited resources to different files in order to minimize the average querying delay. Second, they simply consider storage as available resources for replicas, but neglect the fact that the file holders’ frequency of meeting other nodes also plays an important role in determining file availability. Actually, a node that has a higher meeting frequency with others provides higher availability to its files. This becomes even more evident in sparsely distributed MANETs, in which nodes meet disruptively. In this paper, we introduce a new concept of resource for file replication, which considers both node storage and meeting frequency. We theoretically study the influence of resource allocation on the average querying delay and derive a resource allocation rule to minimize the average querying delay. We further propose a distributed file replication protocol to realize the proposed rule. Extensive trace-driven experiments with synthesized traces and real traces show that our protocol can achieve shorter average querying delay at a lower cost than current replication protocols.

Advances in ubiquitous sensing, computing and wireless communication technologies are leading to the development of cyber-physical systems (CPS), which promise to revolutionize the way we interact with the physical world. CPS applications, such as healthcare monitoring, may involve many users and objects scattered over a wide area. One critical function of CPS is object search in the physical world through the cyber sphere that enables interaction between the cyber and physical spheres. Some of the previously proposed physical object search engines use RFID tracking, and others collect the information of object locations into a hierarchical centralized server. The difficulty of widely deploying RFID devices, the centralized search, and the need for periodical location information collection prevent CPS from achieving higher scalability and efficiency. To deal with this problem, we propose a Social-aware distributed Cyber-Physical human-centric Search engine (SCPS) that leverages the social network formed by wireless device users for object search. Without requiring periodical location information collection, SCPS locates objects held by users based on the routine user movement pattern. Moreover, using a social-aware Bayesian network, it can accurately predict the users’ locations even at the occurrence of exceptional (i.e., non-routine) events (e.g., raining) that break user movement pattern. Thus, SCPS is more advantageous than all previous social network based works which assume that user behaviors always follow a certain pattern. Further, SCPS conducts the search in a fully distributed manner by relying on a distributed hash table (DHT) structure. As a result, SCPS achieves high scalability, efficiency and location accuracy. Extensive real-trace driven simulation results show the superior performance of SCPS compared to other representative search methods including a hierarchical centralized method, a decentralized method, and two social network based methods. The results also show the effectiveness of different components of SCPS.

In this paper, we focus on the efficient routing of data among different areas in delay tolerant networks (DTNs). In current algorithms, packets are forwarded gradually through nodes with higher probability of visiting the destination node or area. However, the number of such nodes usually is limited, leading to insufficient throughput performance. To solve this problem, we propose an inter-landmark data routing algorithm, namely DTN-FLOW. It selects popular places that nodes visit frequently as landmarks and divides the entire DTN area into subareas represented by landmarks. Nodes transiting between landmarks relay packets among landmarks, even though they rarely visit the destinations of these packets. Specifically, the number of node transits between two landmarks is measured to represent the forwarding capacity between them, based on which routing tables are built on each landmark to guide packet routing. Each node predicts its transits based on its previous landmark visiting records using the order- k Markov predictor. When routing a packet, the landmark determines the next-hop landmark based on its routing table and forwards the packet to the node with the highest probability of transiting to the selected landmark. Thus, DTN-FLOW fully utilizes all node movements to route packets along landmark-based paths to their destinations. We analyzed two real DTN traces to support the design of DTN-FLOW. We deployed a small DTN-FLOW system on our campus for performance evaluation. We also proposed advanced extensions to improve its efficiency and stability. The real deployment and trace-driven simulation demonstrate the high efficiency of DTN-FLOW in comparison to state-of-the-art DTN routing algorithms.

Current reputation systems for peer-to-peer (P2P) file sharing networks suffer from high overhead on reputation querying. Also, purely relying on a threshold to detect malicious nodes may make a high-reputed node be reluctant to further increase its reputation in these reputation systems. On the other side, the social network concept of “friendship foster cooperation” can be utilized to alleviate the high overhead in reputation systems. However, the limited number of friends limits the availability of file resources in these approaches. To overcome the drawbacks, we propose a social network based reputation system, namely SocialTrust, that synergistically leverages the social network connections and traditional credit based reputation system to provide efficient reputation management for P2P file sharing. In SocialTrust, each node favors friends for service transactions, which are resulted from both real life acquaintances and online partnerships established between high-reputed and frequently-interacted nodes. When no friends are available for a request, a node chooses the server with the highest reputation. The benefits of friendship and partnership on file sharing and cost saving encourage nodes to be continuously cooperative. Further, SocialTrust considers the number of friends/partners and the reputation of a node in reputation rewarding/punishment in order to realize accurate reputation evaluation. SocialTrust can also prevent certain attacks such as deny of service and collusion. Extensive trace-driven simulation demonstrates the effectiveness of SocialTrust.

In Delay Tolerant Networks (DTNs), nodes meet opportunistically and exchange packets only when they meet with each other. Therefore, routing is usually conducted in a store-carry-forward manner to exploit the scarce communication opportunities. As a result, different packet routing strategies, i.e., which packet to be forwarded or stored with priority, can lead to different routing performance objectives, such as minimal average delay and maximal hit rate. On the other hand, incentive systems are necessary for DTNs since nodes may be selfish and may not be cooperative on packet forwarding/storage. However, current incentive systems for DTNs mainly focus on encouraging nodes to participate in packet forwarding/storage but fail to further encourage nodes to follow a certain packet routing strategy to realize a routing performance objective. We name the former as the first aspect of cooperation and the latter as the second aspect of cooperation in DTN routing. Therefore, in this paper, we first discuss the routing strategy that can realize different performance objectives when nodes are fully cooperative, i.e., are willing to follow both aspects of cooperation. We then propose Multicent, a game theoretical incentive scheme that can encourage nodes to follow the two aspects of cooperation even when they are selfish. Basically, Multicent assigns credits for packet forwarding/storage in proportional to the priorities specified in the routing strategy. Multicent also supports adjustable Quality of Service (QoS) for packet routing between specific sources and destinations. Extensive trace-driven experimental results verify the effectiveness of Multicent.

A peer-to-peer (P2P) file sharing system provides a platform that enables a tremendous number of nodes to share their files. Retrieving desired files efficiently and trustworthily is critical in such a large and jumbled system. However, the issues of efficient searching and trustworthy searching have only been studied separately. Simply combining the methods to achieve the two goals doubles system overhead. In this paper, we first study trace data from Facebook and BitTorrent. Guided by the observations, we propose a system that integrates a social network into a P2P network, named Social-P2P, for simultaneous efficient and trustworthy file sharing. It incorporates three mechanisms: (1) interest/trust-based structure, (2) interest/trust-based file searching, and (3) trust relationship adjustment. By exploiting the social interests and relationships in the social network, the interest/trust-based structure groups common-multi-interest nodes into a cluster and further connects socially close nodes within a cluster. The comparably stable nodes in each cluster form a Distributed Hash Table (DHT) for inter-cluster file searching. In the interest/trust-based file searching mechanism, a file query is forwarded to the cluster of the file by the DHT routing first. Then, it is forwarded along constructed connections within a cluster, which achieves high hit rate and reliable routing. Moreover, sharing files among socially close friends discourages nodes from providing faulty files because people are unlikely to risk their reputation in the real-world. In the trust relationship adjustment mechanism, each node in a routing path adaptively decreases its trust on the node that has forwarded a faulty file in order to avoid routing queries towards misbehaving nodes later on. We conducted extensive trace-driven simulations and implemented a prototype on PlanetLab. Experimental results show that Social-P2P achieves highly efficient and trustworthy file sharing compared to current file sharing systems and trust management systems.

In delay tolerant networks (DTNs), enabling a node to search and find an interested mobile node is an important function in many applications. However, the movement of nodes in DTNs makes the problem formidable. Current methods in disconnected networks mainly rely on fixed stations and infrastructure-based communication to collect node position information, which is difficult to implement in DTNs. In this paper, we present DSearching, a distributed mobile node searching scheme for DTNs that requires no infrastructure except the GPS on mobile nodes. In DSearching, the entire DTN area is split into sub-areas, and each node summarizes its mobility information as both transient sub-area visiting record and long-term movement pattern among sub-areas. Each node distributes its transient visiting record for a newly entered sub-area to nodes that are likely to stay in the sub-area that it just moves out, so that the information flows in the network for the locator to trace it along its actual movement path. Each node also stores different parts of its long-term mobility pattern to long-staying nodes in different sub-areas for the locator to trace it when visiting records are absent. Considering that nodes in DTNs usually have limited resources, DSearching constrains the communication and storage cost in the information distribution process. Extensive trace-driven experiments with real traces demonstrate the high efficiency and high effectiveness of DSearching.

Current peer-to-peer (P2P) file sharing methods in mobile ad hoc networks (MANETs) can be classified into three groups: flooding-based, advertisement-based, and social contact-based. The first two groups of methods can easily have high overhead and low scalability. They are mainly developed for connected MANETs, in which end-to-end connectivity among nodes is ensured. The third group of methods adapts to the opportunistic nature of disconnected MANETs but fails to consider the social interests (i.e., contents) of mobile nodes, which can be exploited to improve the file searching efficiency. In this paper, we propose a P2P content-based file sharing system, namely SPOON, for disconnected MANETs. The system uses an interest extraction algorithm to derive a node's interests from its files for content-based file searching. For efficient file searching, SPOON groups common-interest nodes that frequently meet with each other as communities. It takes advantage of node mobility by designating stable nodes, which have the most frequent contact with community members, as community coordinators for intracommunity searching, and highly mobile nodes that visit other communities frequently as community ambassadors for intercommunity searching. An interest-oriented file searching scheme is proposed for high file searching efficiency. Additional strategies for file prefetching, querying-completion, and loop-prevention, and node churn consideration are discussed to further enhance the file searching efficiency. We first tested our system on the GENI Orbit testbed with a real trace and then conducted event-driven experiment with two real traces and NS2 simulation with simulated disconnected and connected MANET scenarios. The test results show that our system significantly lowers transmission cost and improves file searching success rate compared to current methods.

Previous delay-tolerant network (DTN) routing algorithms exploit either past encounter records or social network properties to derive a node's probability of delivering packets to their destinations. However, they only have a local view of the network, which limits the routing efficiency. Also, when two nodes meet, they have to exchange the delivery abilities to the destinations of all packets in the two nodes, which incurs high resource consumption. In this paper, we propose SMART, which utilizes a distributed social map for lightweight routing in delay-tolerant networks. In SMART, each node builds its own social map consisting of nodes it has met and their frequently encountered nodes in a distributed manner. Based on both encountering frequency and social closeness of the two linked nodes in the social map, we decide the weight of each link to reflect the packet delivery ability between the two nodes. The social map enables more accurate forwarder selection through a broader view. Moreover, nodes exchange much less information for social map update, which reduces resource consumption. Trace-driven experiments and tests on the GENI ORBIT testbed demonstrate the high efficiency of SMART in comparison to previous algorithms.

This paper addresses the data search problem in large-scale highly mobile and dense wireless networks. Current wireless network data search systems are not suitable for large-scale highly mobile and dense wireless networks. This paper presents a scalable and mobility-resilient LOcality-based distRibuted Data search system (LORD) for large-scale wireless networks with high mobility and density. Taking advantage of the high density, rather than mapping data to a location point, LORD maps file metadata to a geographical region and stores it in multiple nodes in the region, thus enhancing mobility-resilience. LORD has a novel region-based geographic data routing protocol that does not rely on flooding or GPSs for data publishing and querying, and a coloring-based partial replication algorithm to reduce data replicas in a region while maintaining the querying efficiency. LORD also works for unbalanced wireless networks with sparse regions. Simulation results show the superior performance of LORD compared to representative data search systems in terms of scalability, overhead, and mobility resilience in a highly dense and mobile network. The results also show the high scalability and mobility-resilience of LORD in an unbalanced wireless network with sparse regions, and the effectiveness of its coloring-based partial replication algorithm.

In current reputation systems for peer-to-peer (P2P) file sharing networks, reputation querying generates high overhead in file service. Also, a high-reputed node may be reluctant to further increase its reputation in these reputation systems. Recently, social network-based P2P systems that favor file sharing among friends have been proposed for reliable file sharing. However, this approach contradicts the objective of widely file sharing in P2P systems. To overcome these drawbacks, we propose a social network integrated reputation system, namely SocialTrust, that synergistically leverages the concept of "friendship fosters cooperation''. In SocialTrust, each node maintains trusted relationships for the purpose of file sharing, which are resulted from both real life acquaintance and online partnership established between high-reputed and frequently-interacted nodes. Given a number of server options, a client first chooses a friend or a partner, if available, without querying their reputations. Otherwise, it chooses the server with the highest reputation. The benefits of friendship and partnership on file sharing and cost saving encourage nodes to be continuously cooperative. Further, in order to realize accurate reputation evaluation and strong cooperation incentives, SocialTrust considers the number of friends/partners and reputation of a node in the process of reputation rewarding and punishment. Extensive trace-driven simulation demonstrates the effectiveness of SocialTrust.

In this paper, we focus on the efficient routing of data among different areas in Delay Tolerant Networks (DTNs). In current algorithms, packets are forwarded gradually through nodes with higher probability of visiting the destination node or area. However, the number of such nodes usually is limited, leading to insufficient throughput performance. To solve this problem, we propose an inter-landmark data routing algorithm, namely DTN-FLOW. It selects popular places that nodes visit frequently as landmarks and divides the entire DTN area into sub-areas represented by landmarks. Nodes transiting between landmarks relay packets among landmarks, even though they rarely visit the destinations of these packets. Specifically, the number of node transits between two landmarks is measured to represent the forwarding capacity between them, based on which routing tables are built on each landmark to guide packet routing. Each node predicts its transits based on its previous landmark visiting records using the order-k Markov predictor. In a packet routing, a landmark determines the next hop landmark based on its routing table, and forwards the packet to the node with the highest probability of transiting to the selected landmark. Thus, DTN-FLOW fully utilizes all node movements to route packets along landmark paths to their destinations. We analyzed two real DTN traces to support the design of DTN-FLOW. We also deployed a small DTN-FLOW system in our campus for performance evaluation. This deployment and trace-driven simulation demonstrate the high efficiency of DTN-FLOW in comparison with state-of-the-art DTN routing algorithms.

Due to intermittent connection and limited communication opportunity, routing in Delay Tolerant Networks (DTNs) is usually conducted in a store-carry-forward manner. Consequently, different packet forwarding or storage strategies can lead to different performance objectives, such as minimal average delay, maximal hit rate, and minimal maximal delay, which are desired by applications with different purposes. However, nodes may not be willing to follow these strategies. Further, selfish nodes may even refuse to carry or forward packets for others if they cannot obtain benefits in return. Though many incentive systems have been proposed to encourage packet forwarding, none of them aim to encourage nodes to realize the aforementioned performance objectives. In this paper, we first discuss the strategies that can realize different performance objectives and then propose Multicent, a game theoretical incentive scheme that not only provides cooperative incentives but also encourages nodes to follow defined rules to realize the desired performance objective. Multicent also makes the Quality of Service (QoS) of packet routing adjustable for specific sources, destinations, or source-destination pairs. Extensive trace-driven experimental results verify the effectiveness of Multicent.

Previous Delay Tolerant Network (DTN) routing algorithms exploit either past encounter records (probabilistic routing) or social network properties (social network based routing) to derive a node's probability of delivering packets to their destinations. However, they only have a local view of the network, which limits the routing efficiency. Also, when two nodes meet, they have to exchange the delivery probabilities to the destinations of all packets in the two nodes, which incurs high resource consumption. In a social network, the people a person frequently meets are usually stable, which makes them play a more important role in forwarding message for the person. Based on this, we propose a lightweight distributed Social MAp based Routing algorithm in delay Tolerant networks (SMART). In SMART, each node builds its own social map consisting of nodes it has met and their frequently encountered nodes in a distributed manner. Based on both encountering frequency and social closeness of the two linked nodes in the social map, we decide the weight of each link to reflect the packet delivery probability between the two nodes. The social map enables more accurate forwarder selection through a broader view. Moreover, nodes exchange much less information for social map update and need fewer updates due to social map stability, which reduces resource consumption. Trace-driven experiments and tests on the GENI ORBIT testbed demonstrate the high efficiency of SMART in comparison with previous algorithms.

File sharing applications in mobile ad hoc networks (MANETs) have attracted more and more attention in recent years. The efficiency of file querying suffers from the distinctive properties of MANETs including node mobility and limited communication range and resource. An intuitive method to alleviate this problem is to create file replicas in the network. However, despite the efforts on file replication, no research has focused on the global optimal replica sharing with minimum average querying delay. Specifically, current file replication protocols in MANETs have two shortcomings. First, they lack a rule to allocate limited resource to different files in order to minimize the average querying delay. Second, they simply consider storage as resource for replicas, but neglect the fact that the file holders' frequency of meeting other nodes also plays an important role in determining file availability. A node having a higher meeting frequency with others provides higher availability to its files. In this paper, we introduce a new concept of resource for file replication, which considers both node storage and meeting frequency. We theoretically study the influence of resource allocation on the average querying delay and derive a resource allocation rule to minimize the average querying delay. We further propose a distributed file replication protocol that follows the rule. The trace-driven experiments on both the real-world GENI testbed and NS-2 show that our protocol can achieve shorter average querying delay at lower cost than current replication protocols, which justifies the correctness of our theoretical analysis and the effectiveness of the proposed protocol.

Current P2P file sharing methods in mobile ad hoc networks (MANETs) can be classified into three groups: flooding-based, advertisement-based and social contact-based. The first two groups of methods can easily generate high overhead and low scalability, and the third group fails to consider the social interests (content) of mobile nodes, which otherwise can improve file searching efficiency. In this paper, we propose a P2P content-based file sharing system for MANETs. The system uses an interest extraction algorithm to derive a node's interests from its files for complex queries. For efficient file searching, it groups common-interest nodes that frequently meet with each other as communities. Further, it takes advantage of node mobility by designating stable nodes, which has frequent contact with community members, as community coordinators for intra-community searching, and highly-mobile nodes as community ambassadors for inter-community searching. An interest-oriented file searching scheme further enhances the file searching success rate. We first deployed our system on the real-world GENI Orbit testbed with a real trace and then conducted experiment on the ns2 simulator with both real trace and simulated disconnected and connected MANET scenario. The test results show that our system significantly lowers transmission cost and improves file searching success rate compared to current methods.