Search

In Named Data Networking, cache pollution, cache poisoning and interest flooding are three popular types of attacks that can drastically degrade the network performance. However, previous methods for mitigating these attacks are not sufficiently effective or efficient. Also, they cannot simultaneously handle the three attacks, or the case that core routers or edge routers are compromised. To handle these problems, we propose an effective and lightweight countermeasure scheme. It consists of token-based router monitoring policy (TRM), hierarchical consensus-based trust management (HCT), and popularity-based probabilistic caching and caching replacement policy (PPC). In TRM, each edge router monitors and evaluates each data requester’s probability of launching the cache pollution attack and each data provider’s probability of launching the cache poisoning attack, and accordingly assigns, rewards and penalizes tokens to them to control their data request and data provision activities. Thus, the interest flooding attack can also be mitigated by limiting the consumption of tokens. In HCT, each core router manages its directly connected edge routers using TRM, and the core routers trust each other through adopting the concept of consensus in Blockchain. Thus, the edge and core routers executing monitoring and evaluation are trustable. PPC uses probabilistic caching and caching replacement based on the popularity of received content to further mitigate the attacks and reduce caching and data verification overhead. Results from simulation experiments demonstrate that our proposed scheme has better performance, in terms of interest satisfaction ratio and average end-to-end delay than current mechanisms. [ABSTRACT FROM AUTHOR]

SIN is constructed to support real-time data acquisition, massive data transmission and processing, and systematized information services. Different from static networks, both the network topologies and the available network resources are dynamic in SIN. However, the existing networking technologies treat SIN as segmented static networks, and ignore the relationship among different segmented subnetworks, which results in low resource utilization and poor transmission QoS. This article exploits the time-varying graph theory to characterize and allocate the dynamic resources of SIN. We first introduce the overall SIN architecture, and discuss its key technologies in terms of network slicing and dynamic routing. Then, we construct a novel STAG to precisely depict the multi-dimensional time-varying resources and reveal their connection relationships in SIN. With STAG, we propose the dynamic network slicing strategy to build the dedicated network slices for different services, and design the intra-slice routing scheme to guarantee the service transmission QoS. Simulation results demonstrate our methods can complete more space missions with higher resource utilization. Finally, we discuss the promising future of the time-varying graph theory. [ABSTRACT FROM AUTHOR]

As the typical delay tolerant networks, the satellite networks possess the intermittent connections, the large-scale time delays and the time-varying topologies. Obviously, such features seriously affect the delivery of mission data with certain requirements on the traffic or latency. To decrease the delivery time, existing relay-based contact graph routing (CGR) method selects the earliest reachable path to forward mission data. However, this method cannot guarantee the transmission of a large amount data and wastes the rare contact opportunities. Therefore, in this paper, we focus on the transmission QoS problem of multiple missions over the satellite networks, and design a QoS support routing strategy to achieve multiple flow-maximizing paths with acceptable delivery delays. Especially, with the storage time aggregated graph (STAG), we construct an on-demand mission model to depict both the network dynamic characteristics and the different mission requirements, and then reduce the QoS support problem as a graph-based maximum flow problem. To solve this problem, one STAG-based multiple flow-maximizing routing scheme is proposed to ensure the mission QoS and match the rare network resources, which has low computation complexity. Finally, compared with CGR, simulation results demonstrate the proposed scheme can achieve a higher mission completion rate and resource utilization rate. [ABSTRACT FROM AUTHOR]

Abstract Delay Tolerant Networks (DTNs) have attracted much research interest recently due to its 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 in DTNs. Therefore, in this paper, we propose a distributed greedy routing algorithm, namely GreedyFlow, for efficient packet routing between landmarks in DTNs. GreedyFlow 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. 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. We also propose advanced components to enhance the consistency of local traffic maps and exploit node-based forwarding, both of which help improve the packet routing efficiency. Extensive real trace driven experiments demonstrate the high efficiency of GreedyFlow. [ABSTRACT FROM AUTHOR]

The multi-commodity flow problem plays an important role in network optimization, routing, and service scheduling. With the network partitioning and the intermittent connectivity, the commodity flows in delay tolerant networks (DTNs) are time-dependent, which is very different from that over the static networks. As an NP-hard problem, existing works can only obtain sub-optimal results on maximizing the multi-commodity flow of dynamic networks. To overcome these bottlenecks, in this paper, we propose a graph-based algorithm to solve the maximum two-commodity flow problem over the DTNs. Through analyzing the relationship between the two commodities, we propose a maximum two-commodity flow theorem to simplify the coupling two-commodity flow problem as the two single-commodity flow ones. Then, with the help of the storage time aggregated graph (STAG) (a DTN model with less memory), we construct a pair of flow graphs to describe the reduced two single-commodity flows (addition flow and subtraction flow), and design the corresponding flow calculation methods. Moreover, we design a STAG-based dynamic combined flow algorithm to maximize the two-commodity flow. Finally, the computational complexity of the proposed algorithm is analyzed, and its efficacy has also been demonstrated through an illustrative example and numerical simulations. [ABSTRACT FROM AUTHOR]

Packet routing is important for vehicular delay tolerant networks (VDTNs). Opportunistic routing algorithms based on historical records are insufficiently accurate in forwarder selection due to movement randomness of vehicles. Trajectory-based routing algorithms tackle vehicle movement randomness but cannot be directly used in VDTNs due to the dependence on APs. In this paper, we develop a distributed trajectory-based routing algorithm (called MobiT) for VDTNs. This non-trivial task faces three challenges. First, vehicle trajectories must be sufficiently collected. Second, the trajectories cannot be updated frequently due to limited resources of the repository nodes. Third, achieving high routing performance even with partially collected trajectories. Our real trace study lays the foundation of the design of MobiT. Taking advantage of different roles of vehicles, MobiT uses service vehicles that move in wide areas to collect vehicle trajectories, and rely on the service vehicles and roadside units (called schedulers) for routing scheduling. By using regular temporal congestion state of road segments, MobiT schedules the packet to arrive at a roadside unit prior to the destination vehicle to improve routing performance. Furthermore, MobiT leverages vehicles’ long-term mobility patterns to assist routing. Our trace-driven simulation and real experiments show the effectiveness and efficiency of MobiT. [ABSTRACT FROM AUTHOR]

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 1) each vehicle has only a few active subareas that it frequently visits, and 2) two frequently encountered vehicles usually encounter each other in their active subareas. We then propose an 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 subarea of the target vehicle using a traffic-aware shortest path spreading algorithm, and then in each subarea, each packet carrier tries to forward the packet to a vehicle that has high encounter frequency with the target vehicle. In addition to the basic AAR, we further propose an advanced AAR (AAAR). In the AAAR, we improve the routing efficiency in each subarea by exploiting spatio-temporal correlation and developing three strategies for calculating spatio-temporal correlation. 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. Also, the simulation shows that our advanced AAAR has better performances than our AAR. [ABSTRACT FROM PUBLISHER]

As a popular routing protocol in wireless sensor networks (WSNs), greedy routing has received great attention. The previous works characterize its data deliverability in WSNs by the probability of all nodes successfully sending their data to the base station. Their analysis, however, neither provides the information of the quantitative relation between successful data delivery ratio and transmission power of sensor nodes nor considers the impact of the network congestion or link collision on the data deliverability. To address these problems, in this paper, we characterize the data deliverability of greedy routing by the ratio of successful data transmissions from sensors to the base station. We introduce $\eta$ -guaranteed delivery which means that the ratio of successful data deliveries is not less than $\eta$ , and study the relationship between the transmission power of sensors and the probability of achieving $\eta$ -guaranteed delivery. Furthermore, with considering the effect of network congestion, link collision, and holes (e.g., those caused by physical obstacles such as a lake), we provide a more precise and full characterization for the deliverability of greedy routing. Extensive simulation and real-world experimental results show the correctness and tightness of the upper bound of the smallest transmission power for achieving $\eta$ -guaranteed delivery. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM PUBLISHER]

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, Cont2 virtually groups common-interest nodes into a community to direct file search. Second, considering human mobility follows a certain pattern, Cont2 exploits nodes' contact frequencies with a community to expedite file searching. To further improve the searching efficiency, Cont2 also 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 Cont2 can effectively improve the search efficiency compared to current methods. [ABSTRACT FROM AUTHOR]

Cooperative adaptive cruise control (CACC) systems have the potential to increase traffic throughput by allowing smaller headway between vehicles and moving vehicles safely in a platoon at a harmonized speed. CACC systems have been attracting significant attention from both academia and industry since connectivity between vehicles will become mandatory for new vehicles in the USA in the near future. In this paper, we review three basic and important aspects of CACC systems: communications, driver characteristics, and controls to identify the most challenging issues for their real-world deployment. Different routing protocols that support the data communication requirements between vehicles in the CACC platoon are reviewed. Promising and suitable protocols are identified. Driver characteristics related issues, such as how to keep drivers engaged in driving tasks during CACC operations, are discussed. To achieve mass acceptance, the control design needs to depict real-world traffic variability such as communication effects, driver behavior, and traffic composition. Thus, this paper also discusses the issues that existing CACC control modules face when considering close to ideal driving conditions. [ABSTRACT FROM PUBLISHER]

Wireless sensor and actuator networks (WSANs) are composed of sensors and actuators to perform distributed sensing and actuating tasks. Most WSAN applications (e.g., fire detection) demand that actuators rapidly respond to observed events. Therefore, real-time (i.e., fast) and fault-tolerant transmission is a critical requirement in WSANs to enable sensed data to reach actuators reliably and quickly. Due to limited power resources, energy-efficiency is another crucial requirement. Such requirements become formidably challenging in large-scale WSANs. However, existing WSANs fall short in meeting these requirements. To this end, we first theoretically study the Kautz graph for its applicability in WSANs to meet these requirements. We then propose a Kautz-based REal-time, Fault-tolerant and EneRgy-efficient WSAN (REFER). REFER embeds Kautz graphs into the physical topology of a WSAN for real-time communication and connects the Kautz graphs using distributed hash table (DHT) for high scalability. We also theoretically study routing paths in the Kautz graph, based on which we develop an efficient fault-tolerant routing protocol. It enables a relay node to quickly and efficiently identify the next shortest path from itself to the destination based only on node IDs upon routing failure, rather than relying on retransmission from the source. REFER is advantageous over previous Kautz graph based works in that it does not need an energy-consuming protocol to find the next shortest path and it preserves the consistency between the overlay and physical topology. We further improve routing in REFER by multi-path based routing and energy-efficient multicasting within and between Kautz graph cells, respectively. Extensive experimental results demonstrate the superior performance of REFER in comparison with existing WSAN systems in terms of real-time communication, energy-efficiency, fault-tolerance and scalability. [ABSTRACT FROM PUBLISHER]

In peer-to-peer file sharing systems, file replication helps to avoid overloading file owners and improve file query efficiency. There exists a tradeoff between minimizing the number of replicas (i.e., replication overhead) and maximizing the replica hit rate (which reduces file querying latency). More replicas lead to increased replication overhead and higher replica hit rates and vice versa. An ideal replication method should generate a low overhead burden to the system while providing low query latency to the users. However, previous replication methods either achieve high hit rates at the cost of many replicas or produce low hit rates. To reduce replicas while guaranteeing high hit rate, this paper presents SWARM, a file replication mechanism based on swarm intelligence. Recognizing the power of collective behaviors, SWARM identifies node swarms with common node interests and close proximity. Unlike most earlier methods, SWARM determines the placement of a file replica based on the accumulated query rates of nodes in a swarm rather than a single node. Replicas are shared by the nodes in a swarm, leading to fewer replicas and high querying efficiency. In addition, SWARM has a novel consistency maintenance algorithm that propagates an update message between proximity-close nodes in a tree fashion from the top to the bottom. Experimental results from the real-world PlanetLab testbed and the PeerSim simulator demonstrate the effectiveness of the SWARM mechanism in comparison with other file replication and consistency maintenance methods. SWARM can reduce querying latency by 40-58 percent, reduce the number of replicas by 39-76 percent, and achieves more than 84 percent higher hit rates compared to previous methods. It also can reduce the consistency maintenance overhead by 49-99 percent compared to previous consistency maintenance methods. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Hybrid wireless networks combining the advantages of both mobile ad-hoc networks and infrastructure wireless networks have been receiving increased attention due to their ultra-high performance. An efficient data routing protocol is important in such networks for high network capacity and scalability. However, most routing protocols for these networks simply combine the ad-hoc transmission mode with the cellular transmission mode, which inherits the drawbacks of ad-hoc transmission. This paper presents a Distributed Three-hop Routing protocol (DTR) for hybrid wireless networks. To take full advantage of the widespread base stations, DTR divides a message data stream into segments and transmits the segments in a distributed manner. It makes full spatial reuse of a system via its high speed ad-hoc interface and alleviates mobile gateway congestion via its cellular interface. Furthermore, sending segments to a number of base stations simultaneously increases throughput and makes full use of widespread base stations. In addition, DTR significantly reduces overhead due to short path lengths and the elimination of route discovery and maintenance. DTR also has a congestion control algorithm to avoid overloading base stations. Theoretical analysis and simulation results show the superiority of DTR in comparison with other routing protocols in terms of throughput capacity, scalability, and mobility resilience. The results also show the effectiveness of the congestion control algorithm in balancing the load between base stations. [ABSTRACT FROM AUTHOR]

Efficient file query is important to the overall performance of peer-to-peer (P2P) file sharing systems. Clustering peers by their common interests can significantly enhance the efficiency of file query. Clustering peers by their physical proximity can also improve file query performance. However, few current works are able to cluster peers based on both peer interest and physical proximity. Although structured P2Ps provide higher file query efficiency than unstructured P2Ps, it is difficult to realize it due to their strictly defined topologies. In this work, we introduce a Proximity-Aware and Interest-clustered P2P file sharing System (PAIS) based on a structured P2P, which forms physically-close nodes into a cluster and further groups physically-close and common-interest nodes into a sub-cluster based on a hierarchical topology. PAIS uses an intelligent file replication algorithm to further enhance file query efficiency. It creates replicas of files that are frequently requested by a group of physically close nodes in their location. Moreover, PAIS enhances the intra-sub-cluster file searching through several approaches. First, it further classifies the interest of a sub-cluster to a number of sub-interests, and clusters common-sub-interest nodes into a group for file sharing. Second, PAIS builds an overlay for each group that connects lower capacity nodes to higher capacity nodes for distributed file querying while avoiding node overload. Third, to reduce file searching delay, PAIS uses proactive file information collection so that a file requester can know if its requested file is in its nearby nodes. Fourth, to reduce the overhead of the file information collection, PAIS uses bloom filter based file information collection and corresponding distributed file searching. Fifth, to improve the file sharing efficiency, PAIS ranks the bloom filter results in order. Sixth, considering that a recently visited file tends to be visited again, the bloom filter based approach is enhanced by only checking the newly added bloom filter information to reduce file searching delay. Trace-driven experimental results from the real-world PlanetLab testbed demonstrate that PAIS dramatically reduces overhead and enhances the efficiency of file sharing with and without churn. Further, the experimental results show the high effectiveness of the intra-sub-cluster file searching approaches in improving file searching efficiency. [ABSTRACT FROM PUBLISHER]

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. [ABSTRACT FROM PUBLISHER]

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. [ABSTRACT FROM AUTHOR]

In a hybrid wireless network that combines a mobile ad-hoc network and an infrastructure network, efficient and reliable data routing is important for high throughput. Existing routing schemes that simply combine ad-hoc and infrastructure routings inherit the drawbacks of ad-hoc routing including congestion and high overhead for route discovery and maintenance. Although current reputation systems help increase routing reliability, they rely on local information exchanges between nodes to evaluate node reputations, so they are not sufficiently effective and efficient. A challenge here is if we can coordinately develop an efficient routing algorithm and effective cooperation incentives for reliable routing. To handle this challenge, this paper presents a peer-to-peer (P2P)-based Market-guided Distributed Routing mechanism (MDR). MDR takes advantage of widespread base stations to coordinately realize highly efficient data routing, and effective reputation management and trading market management for reliable data routing. The packets from a source node are distributively transmitted to base stations directly or indirectly, and then they are transmitted to the destination. The base stations form a P2P structure for reputation collection and querying to avoid local information exchanges, and for managing the service transactions between nodes in the trading market. By leveraging the single-relay transmission feature, base stations can monitor the actual transmitted packets of relay nodes to more accurately and efficiently evaluate their reputations and execute trading market management, as well as detect falsely reported reputation information. We further propose market-based policies to strengthen cooperation incentives. Simulation results show that MDR outperforms the traditional hybrid routing schemes and reputation systems in achieving high throughput. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM PUBLISHER]

Encouraging cooperation and deterring selfish behaviors are important for proper operations of mobile ad hoc networks (MANETs). For this purpose, most previous efforts rely on either reputation systems or price systems. However, these systems are neither sufficiently effective in providing cooperation incentives nor sufficiently efficient in resource consumption. Nodes in both systems can be uncooperative while still being considered trustworthy. Also, information exchange between mobile nodes in reputation systems and credit circulation in price systems consumes significant resources. This paper presents a hierarchical Account-aided Reputation Management system (ARM) to efficiently and effectively provide cooperation incentives. ARM builds a hierarchical locality-aware distributed hash table (DHT) infrastructure for efficient and integrated operation of both reputation and price systems. The infrastructure helps to globally collect all node reputation information in the system, which can be used to calculate more accurate reputation and detect abnormal reputation information. Also, ARM integrates reputation and price systems by enabling higher-reputed nodes to pay less for their received services. Theoretical analysis demonstrates the properties of ARM. Simulation results show that ARM outperforms the individual reputation system and price system in terms of effectiveness and efficiency of providing cooperation incentives and deterring selfish behaviors. [ABSTRACT FROM PUBLISHER]

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. [ABSTRACT FROM PUBLISHER]

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. [ABSTRACT FROM AUTHOR]

As wireless communication gains popularity, significant research has been devoted to supporting real-time transmission with stringent Quality of Service (QoS) requirements for wireless applications. At the same time, a wireless hybrid network that integrates a mobile wireless ad hoc network (MANET) and a wireless infrastructure network has been proven to be a better alternative for the next generation wireless networks. By directly adopting resource reservation-based QoS routing for MANETs, hybrids networks inherit invalid reservation and race condition problems in MANETs. How to guarantee the QoS in hybrid networks remains an open problem. In this paper, we propose a QoS-Oriented Distributed routing protocol (QOD) to enhance the QoS support capability of hybrid networks. Taking advantage of fewer transmission hops and anycast transmission features of the hybrid networks, QOD transforms the packet routing problem to a resource scheduling problem. QOD incorporates five algorithms: 1) a QoS-guaranteed neighbor selection algorithm to meet the transmission delay requirement, 2) a distributed packet scheduling algorithm to further reduce transmission delay, 3) a mobility-based segment resizing algorithm that adaptively adjusts segment size according to node mobility in order to reduce transmission time, 4) a traffic redundant elimination algorithm to increase the transmission throughput, and 5) a data redundancy elimination-based transmission algorithm to eliminate the redundant data to further improve the transmission QoS. Analytical and simulation results based on the random way-point model and the real human mobility model show that QOD can provide high QoS performance in terms of overhead, transmission delay, mobility-resilience, and scalability. [ABSTRACT FROM PUBLISHER]

Mobile Ad Hoc Networks (MANETs) use anonymous routing protocols that hide node identities and/or routes from outside observers in order to provide anonymity protection. However, existing anonymous routing protocols relying on either hop-by-hop encryption or redundant traffic, either generate high cost or cannot provide full anonymity protection to data sources, destinations, and routes. The high cost exacerbates the inherent resource constraint problem in MANETs especially in multimedia wireless applications. To offer high anonymity protection at a low cost, we propose an Anonymous Location-based Efficient Routing proTocol (ALERT). ALERT dynamically partitions the network field into zones and randomly chooses nodes in zones as intermediate relay nodes, which form a nontraceable anonymous route. In addition, it hides the data initiator/receiver among many initiators/receivers to strengthen source and destination anonymity protection. Thus, ALERT offers anonymity protection to sources, destinations, and routes. It also has strategies to effectively counter intersection and timing attacks. We theoretically analyze ALERT in terms of anonymity and efficiency. Experimental results exhibit consistency with the theoretical analysis, and show that ALERT achieves better route anonymity protection and lower cost compared to other anonymous routing protocols. Also, ALERT achieves comparable routing efficiency to the GPSR geographical routing protocol. [ABSTRACT FROM AUTHOR]

Resource discovery is critical to the usability and accessibility of grid computing systems. Distributed Hash Table (DHT) has been applied to grid systems as a distributed mechanism for providing scalable range-query and multi-attribute resource discovery. Multi-DHT-based approaches depend on multiple DHT networks with each network responsible for a single attribute. Single-DHT-based approaches keep the resource information of all attributes in a single node. Both classes of approaches lead to high overhead. In this paper, we propose a Low-Overhead Range-query Multi-attribute (LORM) DHT-based resource discovery approach. Unlike other DHT-based approaches, LORM relies on a single compound graph-based DHT network and distributes resource information among nodes in balance by taking advantage of the compound graph structure. Moreover, it has high capability to handle the large-scale and dynamic characteristics of resources in grids. Experimental results demonstrate the efficiency of LORM in comparison with other resource discovery approaches. LORM dramatically reduces maintenance and resource discovery overhead. In addition, it yields significant improvements in resource location efficiency. We also analyze the performance of the LORM approach rigorously by comparing it with other multi-DHT-based and single-DHT-based approaches with respect to their overhead and efficiency. The analytical results are consistent with experimental results, and prove the superiority of the LORM approach in theory. [ABSTRACT FROM AUTHOR]

Since centralized data storage and search schemes often lead to high overhead and latency, distributed data-centric storage becomes a preferable approach in large-scale wireless sensor networks (WSNs). However, most of existing distributed methods lack optimization for spatial-temporal search to query events occurred in a certain geographical area and a certain time period. Furthermore, for data search routing, most methods rely on locating systems (e.g., GPS), which consume high energy. This paper proposes a distributed spatial-temporal Similarity Data Storage (SDS) scheme. SDS provides efficient spatial-temporal and similarity data searching service, and is applicable for both static and dynamic WSNs. It disseminates event data in such a way that the distance between WSN neighborhoods represents the similarity of data stored in them. In addition, SDS carpooling routing algorithm efficiently routes messages without the aid of GPS. Theoretical and experimental results show that SDS yields significant improvements on the efficiency of data querying compared with existing approaches, and obtains stable performance in dynamic environments. [ABSTRACT FROM AUTHOR]