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Optimal stochastic control of delay tolerant networks is studied in this paper. First, the structure of optimal two-hop forwarding policies is derived. In order to be implemented, such policies require knowledge of certain global system parameters such as the number of mobiles or the rate of contacts between mobiles. But, such parameters could be unknown at system design time or may even change over time. In order to address this problem, adaptive policies are designed that combine estimation and control: based on stochastic approximation techniques, such policies are proved to achieve optimal performance in spite of lack of global information. Furthermore, the paper studies interactions that may occur in the presence of several DTNs which compete for the access to a gateway node. The latter problem is formulated as a cost-coupled stochastic game and a unique Nash equilibrium is found. Such equilibrium corresponds to the system configuration in which each DTN adopts the optimal forwarding policy determined for the single network problem. [ABSTRACT FROM AUTHOR]

Mobile Opportunistic Networks (MONs) are characterized by intermittent connectivity with long isolation period, and nodes following redundant transmissions for reliable message delivery. This often leads to unnecessary buffer occupancy, preventing new messages from getting replicated due to small contact duration and low bandwidth, or leading to packet drop under constrained buffer. Although attempts have been made to mitigate buffer congestion, the existing schemes are localized, are slow to react, or are specific to a routing scheme. Moreover, they rely on message exchanges to obtain buffer state/occupancy, thereby incurring additional overhead. In this paper, we first develop a generalized probabilistic forwarding model where the forwarding probability denotes the likelihood of a message to get forwarded to the encountered node. Based on the forwarding probability, we develop a congestion indicator and predict the point of congestion using the Kalman filter. Using this, a node can decide the optimal number and the exact set of messages to replicate, which leads to an optimal performance with minimal packet drop and overhead. Simulation results using a synthetic mobility model and a real-life mobility trace show that the proposed scheme outperforms the existing schemes. [ABSTRACT FROM AUTHOR]

In this paper, a joint optimization of link scheduling, routing and replication for delay-tolerant networks (DTNs) has been studied. The optimization problems for resource allocation in DTNs are typically solved using dynamic programming which requires knowledge of future events such as meeting schedules and durations. This paper defines a new notion of approximation to the optimality for DTNs, called snapshot approximation where nodes are not clairvoyant, i.e., not looking ahead into future events, and thus decisions are made using only contemporarily available knowledges. Unfortunately, the snapshot approximation still requires solving an NP-hard problem of maximum weighted independent set (MWIS) and a global knowledge of who currently owns a copy and what their delivery probabilities are. This paper proposes an algorithm, Max-Contribution (MC) that approximates MWIS problem with a greedy method and its distributed online approximation algorithm, Distributed Max-Contribution (DMC) that performs scheduling, routing and replication based only on locally and contemporarily available information. Through extensive simulations based on real GPS traces tracking over 4,000 taxies and 500 taxies for about 30 days and 25 days in two different large cities, DMC is verified to perform closely to MC and outperform existing heuristically engineered resource allocation algorithms for DTNs. [ABSTRACT FROM AUTHOR]

Densification through small cells and caching in base stations have been proposed to deal with the increasing demand for Internet content and the related overload on the cellular infrastructure. However, these solutions are expensive to install and maintain. Instead, using vehicles acting as mobile caches might represent an interesting alternative. In our work, we assume that users can query nearby vehicles for some time, and be redirected to the cellular infrastructure when the deadline expires. Beyond reducing costs, in such an architecture, through vehicle mobility, a user sees a much larger variety of locally accessible content within only few minutes. Unlike most of the related works on delay tolerant access, we consider the impact on the user experience by assigning different retrieval deadlines per content. In our paper, we provide the following contributions: (i) we model analytically such a scenario; (ii) we formulate an optimization problem to maximize the traffic offloaded while ensuring user experience guarantees; (iii) we propose two variable deadline policies; (iv) we perform realistic trace-based simulations, and we show that, even with low technology penetration rate, more than 60 percent of the total traffic can be offloaded which is around 20 percent larger compared to existing allocation policies. [ABSTRACT FROM AUTHOR]

The dramatic growth of mobile application usage has posed great pressure on application developers to better manage their backend capacity. Rule-based or schedule-based auto-scaling mechanisms have been proposed, but it is difficult or expensive to frequently adjust the backend capacity to track the burstiness of mobile traffic. In this paper, we explore a fundamentally different approach. Instead of scaling the backend in line with the mobile traffic, we smooth out traffic profiles to reduce the required backend capacity and increase its utilization. Our proposed solution, called Razor, is inspired by two key insights on mobile traffic. First, mobile traffic exhibits high short-term fluctuations but steady long-term trend, so that we may temporarily delay user requests and periodically adapt backend capacity based on the predicted traffic volume. Second, user requests have different priorities: while some requests are urgent (e.g., sending a message), some are delay-tolerant (e.g., changing the profile photo) and can be postponed without much influence on the user experience. Based on these observations, our design features a two-tier architecture: on a long timescale, Razor predicts future traffic using machine learning algorithms and plans the optimal backend capacity to minimize the budget with performance guarantee; on a short timescale, Razor schedules which requests to delay and by how much time to delay according to their delay tolerance. We implement a fully-functional prototype of Razor, and evaluate its performance with both real and synthetic traces. Extensive experimental results show that Razor can effectively help mobile application developers reduce their backend cost while guaranteeing the user experience. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM PUBLISHER]

Delay tolerant networks (DTNs) recently have drawn much attention from researchers due to their wide applications in various challenging environments. Previous DTN research mainly concentrates on information propagation and packet delivery. However, with possible participation of a large number of mobile devices, how to maintain efficient and dynamic topology becomes crucial. In this paper, we study the topology design problem in a predictable DTN where the time-evolving topology is known a priori or can be predicted. We model such a time-evolving network as a weighted directed space-time graph which includes both spacial and temporal information. Links inside the space-time graph are unreliable due to either the dynamic nature of wireless communications or the rough prediction of underlying human/device mobility. The purpose of our reliable topology design problem is to build a sparse structure from the original space-time graph such that (1) for any pair of devices, there is a space-time path connecting them with a reliability higher than the required threshold; (2) the total cost of the structure is minimized. Such an optimization problem is NP-hard, thus we propose several heuristics which can significantly reduce the total cost of the topology while maintain the “reliable” connectivity over time. In this paper, we consider both unicast and broadcast reliability of a topology. Finally, extensive simulations are conducted on random DTNs, a synthetic space DTN, and a real-world DTN tracing data. Results demonstrate the efficiency of the proposed methods. [ABSTRACT FROM AUTHOR]

Many applications, such as product promotion advertisement and traffic congestion notification, benefit from opportunistic content exchange in Delay Tolerant Networks (DTNs). An important requirement of such applications is timely delivery. However, the intermittent connectivity of DTNs may significantly delay content exchange, and cannot guarantee timely delivery. The state-of-the-arts capture mobility patterns or social properties of mobile devices. Such solutions do not capture patterns of delivered content in order to optimize content delivery. Without such optimization, the content demanded by a large number of subscribers could follow the same forwarding path as the content by only one subscriber, leading to traffic congestion and packet drop. To address the challenge, in this paper, we develop a solution framework, namely Ameba, for timely delivery. In detail, we first leverage content properties to derive an optimal routing hop count of each content to maximize the number of needed nodes. Next, we develop node utilities to capture interests, capacity and locations of mobile devices. Finally, the distributed forwarding scheme leverages the optimal routing hop count and node utilities to deliver content towards the needed nodes in a timely manner. Illustrative results verify that Ameba achieves comparable delivery ratio as Epidemic but with much lower overhead. [ABSTRACT FROM PUBLISHER]

Propagation of faulty data is a critical issue. In case of Delay Tolerant Networks (DTN) in particular, the rare meeting events require that nodes are efficient in propagating only correct information. For that purpose, mechanisms to rapidly identify possible faulty nodes should be developed. Distributed faulty node detection has been addressed in the literature in the context of sensor and vehicular networks, but already proposed solutions suffer from long delays in identifying and isolating nodes producing faulty data. This is unsuitable to DTNs where nodes meet only rarely. This paper proposes a fully distributed and easily implementable approach to allow each DTN node to rapidly identify whether its sensors are producing faulty data. The dynamical behavior of the proposed algorithm is approximated by some continuous-time state equations, whose equilibrium is characterized. The presence of misbehaving nodes, trying to perturb the faulty node detection process, is also taken into account. Detection and false alarm rates are estimated by comparing both theoretical and simulation results. Numerical results assess the effectiveness of the proposed solution and can be used to give guidelines for the algorithm design. [ABSTRACT FROM PUBLISHER]

Communications in vehicular ad-hoc network (VANET) are subject to performance degradation as results of channel fading and intermittent network connectivity. The emerging Vehicular Content Centric Network (VCCN) is promising in supporting the needs of contents and alleviating the communication problems in VANET. Specifically, to improve the cache hit ratio and reduce the access delay of content retrieval, it helps to choose the appropriate vehicles to cache the frequently accessed data items. In this paper, we propose a Cooperative Caching scheme based on Social Attributes and Mobility Prediction (CCSAMP) for VCCN. CCSAMP is based on the observation that vehicles move around and are liable to contact each other according to drivers’ common interests or social similarities. A caching node sharing more social attributes with the content requester is more likely to be interested in the same contents and distribute the contents to others with similar interests. Furthermore, a caching node that frequently meets other nodes is a better candidate to keep cache copies. To increase the network performance, CCSAMP also exploits the regularity of vehicle moving behaviors to predict the chance for a vehicle to reach hot zones based on Hidden Markov Model (HMM). We evaluate CCSAMP through the ONE simulator to demonstrate its higher cache hit ratio and lower content access delay compared to other state-of-the-art schemes. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Mobile crowdsensing is a new paradigm in which a crowd of mobile users exploit their carried smart phones to conduct complex sensing tasks. In this paper, we focus on the makespan sensitive task assignment problems for the crowdsensing in mobile social networks, where the mobility model is predicable, and the time of sending tasks and recycling results is non-negligible. To solve the problems, we propose an Average makespan sensitive Online Task Assignment (AOTA) algorithm and a Largest makespan sensitive Online Task Assignment (LOTA) algorithm. In AOTA and LOTA, the online task assignments are viewed as multiple rounds of virtual offline task assignments. Moreover, a greedy strategy of small-task-first-assignment and earliest-idle-user-receive-task is adopted for each round of virtual offline task assignment in AOTA, while the greedy strategy of large-task-first-assignment and earliest-idle-user-receive-task is adopted for the virtual offline task assignments in LOTA. Based on the two greedy strategies, both AOTA and LOTA can achieve nearly optimal online decision performances. We prove this and give the competitive ratios of the two algorithms. In addition, we also demonstrate the significant performance of the two algorithms through extensive simulations, based on four real MSN traces and a synthetic MSN trace. [ABSTRACT FROM AUTHOR]

The message replication strategy, namely the way message copies are generated and diffused (a.k.a. sprayed) in the network, is a fundamental, yet not thoroughly explored, component of all multi-copy message forwarding schemes in opportunistic networks. Whereas almost all related protocols rely to some extent on the assistance of intermediate nodes for relaying message copies towards their destination, the generation of new message copies may either involve them or be carried out exclusively by the message source. This paper first formulates and solves analytical models for the performance of the two most popular message spraying strategies under imperfect node cooperation and homogeneous exponentially distributed pairwise node inter-contact times. Numerical results suggest that as the node cooperation decreases source replication consistently outperforms binary replication, i.e., the optimal variant of intermediate node-assisted replication under nominal conditions of full node cooperation. The analytical conclusions are also verified for more realistic node mobility patterns through trace-driven experimentation. We then formulate the ideal selection of replication mode as a finite-horizon Continuous Time Markov Decision Process with restricted decision epochs and solve it for the optimal spraying policy. The optimal policy coincides with the binary-(source-) spraying in the presence of few (resp. many) misbehaving nodes. To better approximate it at intermediate levels of misbehavior intensity, we introduce and analyze a simple static spraying policy permitting source-destination space-time paths of up to three hops. Our work deepens the understanding of a core operation embedded in a broad range of multi-copy DTN forwarding protocols. At the same time, it advocates a more thorough approach to the design and evaluation of DTN forwarding that accounts for beyond-nominal conditions. [ABSTRACT FROM AUTHOR]

Due to instability of links in the network, the model of delay tolerant networks (DTNs) is often adopted in many emerging mobile applications. To organizations and individuals using these mobile applications, security and privacy are considered to be two of the most significant concerns. This research seeks to address anonymous communications in DTNs. While many different anonymous routing protocols have been proposed for ad hoc networks, to the best of our knowledge, only variants of onion-based routing have been tailored for DTNs. Since each type of anonymous routing protocol has its pros and cons, there is no single anonymous routing protocol for DTNs that can adapt to the different levels of security requirements. In this paper, we first design a set of anonymous routing protocols for DTNs, called anonymous Epidemic and zone-based anonymous routing, based on the original anonymous routing protocols for ad hoc networks. Then, we propose a framework of anonymous routing (FAR) for DTNs, which subsumes all the aforementioned protocols. By tuning its parameters, the proposed FAR is able to outperform onion-based, anonymous Epidemic, and zone-based routing. In addition, numerical analyses for the traceable rate, node anonymity, and path anonymity models are built. Extensive simulations using randomly generated graphs as well as real traces demonstrate that the proposed framework for DTNs successfully achieves its design goals. [ABSTRACT FROM AUTHOR]

This paper characterizes the throughput and delay performance of Cognitive Radio Networks (CRNs), where both primary and secondary networks coexist in a unit torus. Specifically, the primary network consists of static primary nodes (PNs) of density $n$ n , which have a higher priority to access the spectrum. In contrast, the secondary network consists of mobile secondary nodes (SNs) of density $m=n^{\beta }$ m = n β with $\beta \geq 1$ β ≥ 1 , which move according to a hybrid random walk mobility model and have opportunistic access to the spectrum without affecting primary packet transmissions. Motivated by the fact that cooperation between primary and secondary nodes leads to possible improvement on the performance of CRNs, as well as the fact that the heterogeneous moving regions of secondary nodes will bring about further improvement, we propose a novel hierarchical cooperative scheduling mechanism, where secondary nodes serve as relays for primary packet transmissions by exploiting their mobility heterogeneity and geographic information. Our findings include: (i) For the primary network, stronger mobility heterogeneity of secondary nodes leads to better delay performance of the primary network, and meanwhile the delay scaling can be significantly reduced to $\Theta (n^{\sqrt{\beta /{(4\;\log n)}}}\log ^{3/2}n)$ Θ (n β / (4 log n) log 3 / 2 n) when a near-optimal per-node throughput of $\Theta ({1}/{\log n})$ Θ (1 / log n) is obtained. (ii) For the secondary network, we also adopt a similar hierarchical cooperative scheduling mechanism, and obtain a near-optimal per-node throughput of $\Theta {(1/{\log m})}$ Θ (1 / log m) with the delay scaling of $\Theta ({m^{1-(1/\sqrt{\log m})}})$ Θ (m 1 - (1 / log m)) . (iii) The delay of secondary source-destination pairs is determined by the moving region of destinations and has no relation with sources. Our work provides deeper understandings of the cooperation, heterogeneous mobility, and geographic information on the performance of CRNs, and sheds light on designing more efficient CRNs. [ABSTRACT FROM AUTHOR]

Underwater optical wireless links have limited range and intermittent connectivity due to the hostile aquatic channel impairments and misalignment between the optical transceivers. Therefore, multi-hop communication can expand the communication range, enhance network connectivity, and provide a more precise network localization scheme. In this regard, this paper investigates the connectivity of underwater optical wireless sensor networks (UOWSNs) and its impacts on the network localization performance. First, we model UOWSNs as randomly scaled sector graphs where the connection between sensors is established by point-to-point directed links. Thereafter, the probability of network connectivity is analytically derived as a function of network density, communication range, and optical transmitters' divergence angle. Second, the network localization problem is formulated as an unconstrained optimization problem and solved using the conjugate gradient technique. Numerical results show that different network parameters such as the number of nodes, divergence angle, and transmission range significantly influence the probability of a connected network. Furthermore, the performance of the proposed localization technique is compared to well-known network localization schemes and the results show that the localization accuracy of the proposed technique outperforms the literature in terms of network connectivity, ranging error, and number of anchors. [ABSTRACT FROM AUTHOR]

Delay Tolerant Network (DTN) is developed to cope with intermittent connectivity and long delay in wireless networks. Due to the limited connectivity, DTN is vulnerable to blackhole and greyhole attacks in which malicious nodes intentionally drop all or part of the received messages. Although existing proposals could accurately detect the attack launched by individuals, they fail to tackle the case that malicious nodes cooperate with each other to cheat the defense system. In this paper, we suggest a scheme called Statistical-based Detection of Blackhole and Greyhole attackers (SDBG) to address both individual and collusion attacks. Nodes are required to exchange their encounter record histories, based on which other nodes can evaluate their forwarding behaviors. To detect the individual misbehavior, we define forwarding ratio metrics that can distinguish the behavious of attackers from normal nodes. Malicious nodes might avoid being detected by colluding to manipulate their forwarding ratio metrics. To continuously drop messages and promote the metrics at the same time, attackers need to create fake encounter records frequently and with high forged numbers of sent messages. We exploit the abnormal pattern of appearance frequency and number of sent messages in fake encounters to design a robust algorithm to detect colluding attackers. Extensive simulation shows that our solution can work with various dropping probabilities and different number of attackers per collusion at high accuracy and low false positive. [ABSTRACT FROM AUTHOR]

Accurately determining the network energy consumption of each software principal when multiple ones are active is the key to mobile energy optimization. Tail energy accounting, which attributes tail energy to individual software principals, remains an open problem. Besides, tail energy has also become a major energy drain, especially in mobile ad modules that generate frequent, intermittent network traffics by on-demand ad downloading. In this paper, we propose a systematic framework for mobile ad prefetching and energy optimization, based on a novel tail energy accounting policy using cooperative game theory. In particular, we maximize the sum of deadline- and energy-aware ad utility, by jointly determining apps' aggressiveness in ad prefetching. The proposed tail energy accounting not only characterizes the energy profile of each app's ad module, a crucial input in energy optimization, but also enables an efficient solution by decoupling decision making of individual apps. The proposed framework is implemented on Android with negligible performance/network overhead. Using real-world apps and usage traces, we demonstrate a significant reduction in mobile network energy consumption by up to 45 percent compared with existing approaches. To the best of our knowledge, it is the first fully implemented ad management system transparent to apps and ad ecosystem. [ABSTRACT FROM AUTHOR]

Cellular networks (e.g., 3G) are currently facing severe traffic overload problems caused by excessive traffic demands. Offloading part of the cellular traffic through other forms of networks, such as Delay Tolerant Networks (DTNs) and WiFi hotspots, is a promising solution. However, since these networks can only provide intermittent connectivity to mobile users, utilizing them for cellular traffic offloading may result in a nonnegligible delay. As the delay increases, the users' satisfaction decreases. In this paper, we investigate the tradeoff between the amount of traffic being offloaded and the users' satisfaction. We provide a novel incentive framework to motivate users to leverage their delay tolerance for cellular traffic offloading. To minimize the incentive cost given an offloading target, users with high delay tolerance and large offloading potential should be prioritized for traffic offloading. To effectively capture the dynamic characteristics of users' delay tolerance, our incentive framework is based on reverse auction to let users proactively express their delay tolerance by submitting bids. We further illustrate how to predict the offloading potential of the users by using stochastic analysis for both DTN and WiFi cases. Extensive trace-driven simulations verify the efficiency of our incentive framework for cellular traffic offloading. [ABSTRACT FROM PUBLISHER]

A large body of work has theoretically analyzed the performance of mobility-assisted routing schemes for intermittently connected mobile networks, However, the vast majority of these prior studies have ignored wireless contention. Recent papers have shown through simulations that ignoring contention leads to inaccurate and misleading results, even for sparse networks. In this paper, we analyze the performance of routing schemes under contention. First, we introduce a mathematical framework to model contention. This framework can be used to analyze any routing scheme with any mobility and channel model. Then, we use this framework to compute the expected delays for different representative mobility-assisted routing schemes under random direction, random waypoint, and community-based mobility models. Finally, we use these delay expressions to optimize the design of routing schemes while demonstrating that designing and optimizing routing schemes using analytical expressions that ignore contention can lead to suboptimal or even erroneous behavior. [ABSTRACT FROM AUTHOR]

For disconnected Vehicular Ad hoc NETworks (VANETs), the carry-and-forward mechanism is promising to ensure the delivery success ratio at the cost of a longer delay, as the vehicle travel speed is much lower than the wireless signal propagation speed. Estimating delay is critical to select the paths with low delay, and is also challenging given the random topology and high mobility, and the difficulty to let the message propagate along the selected path. In this paper, we first propose a simple yet effective propagation strategy considering bidirectional vehicle traffic for two-dimensional VANETs, so the opposite-direction vehicles can be used to accelerate the message propagation and the message can largely follow the selected path. Focusing on the propagation delay, an analytical framework is developed to quantify the expected path delay. Using the analytical model, a source node can apply the shortest-path algorithm to select the path with the lowest expected delay. Performance evaluation by simulation show that, when the vehicle density is uneven but known, the proposed Minimum Delay Routing Algorithm can achieve a substantial reduction in delay compared with the geocast-routing approach, and its performance is close to the flooding-based Epidemic algorithm, while our solution maintains only a single copy of the message. [ABSTRACT FROM AUTHOR]

Opportunistic networks enable mobile devices to communicate with each other through routes that are built dynamically, while messages are en route between the sender and the destination(s). The social structure and interaction of users of such devices dictate the performance of routing protocols in those networks. Community structures, commonly exhibited by social networks, is also observed in the encounter patterns in opportunistic networks and has an astounding impact in designing forwarding algorithms for such types of networks. In this paper, we explore the structural vulnerability of social-based forwarding and routing methods in opportunistic networks. In particular, we introduce Community Vulnerability Assessment (CVA), a new problem on assessing the performance reliability of opportunistic routing strategies in Delay Tolerant Networks (DTN) from a community structure point of view. Given a positive number $k$ , CVA aims to find out the $k$ most vulnerable devices in the network whose non-participation (due to out-of-service or permanent out-of-range) transforms the current network community structure to a totally different one. As the first study in this direction, we analyze and provide key insights into the separation of network communities, evaluated via the Normalized Mutual Information (NMI). Based on these findings, we suggest an approximation algorithm for the special case when, and a heuristic, genEdge, for the general case. To certify the effectiveness of our proposed approaches, we first test them on synthesized data with known community structures, and then we show the impact of node removal on community structures in real social networks. Finally we evaluate the performance via different forwarding and routing strategies in multiple real-world DTN traces. Our results indicate that, in many forwarding and routing methods, the nonparticipation of only some important devices is significant enough to degrade the entire network's performance. [ABSTRACT FROM AUTHOR]

Mobile ad-hoc networks (MANETs) assume that mobile nodes voluntary cooperate in order to work properly. This cooperation is a cost-intensive activity and some nodes can refuse to cooperate, leading to a selfish node behaviour. Thus, the overall network performance could be seriously affected. The use of watchdogs is a well-known mechanism to detect selfish nodes. However, the detection process performed by watchdogs can fail, generating false positives and false negatives that can induce to wrong operations. Moreover, relying on local watchdogs alone can lead to poor performance when detecting selfish nodes, in term of precision and speed. This is specially important on networks with sporadic contacts, such as delay tolerant networks (DTNs), where sometimes watchdogs lack of enough time or information to detect the selfish nodes. Thus, we propose collaborative contact-based watchdog (CoCoWa) as a collaborative approach based on the diffusion of local selfish nodes awareness when a contact occurs, so that information about selfish nodes is quickly propagated. As shown in the paper, this collaborative approach reduces the time and increases the precision when detecting selfish nodes. [ABSTRACT FROM AUTHOR]

Content dissemination is very useful for many mobile applications, like instant messaging, file sharing, and advertisement broadcast, etc. In real life, for various kinds of time-insensitive contents, such as family photos and video clips, the process of content dissemination forms a delay tolerant networks (DTNs). To improve the data forwarding performance in DTNs, several social-based approaches have been proposed, most of which leverage mobile users’ social information, including contact history, moving trajectory, and personal profiles as metrics to design routing schemes. However, although the social-based approaches provide better performance, the revealing of mobile users’ information apparently compromises their privacy. Moreover, users’ contents may only be shared with a particular group of users rather everyone in the system. In this paper, we propose the PSaD: a Privacy-preserving Social-assisted content Dissemination scheme in DTNs. We apply users’ verifiable attributes to establish their social relationships in terms of identical attributes in a privacy-preserving way. Besides, to provide the confidentiality of contents, our approach enables users to encrypt contents before the dissemination process, and only allows users who have particular attributes to decrypt them. Bytrace-driven simulations and experiments, we show the performance, privacy preservation, and efficiency of our proposed scheme. [ABSTRACT FROM AUTHOR]

Road networks have significant impact on mobility and network characteristics of wireless ad hoc networks. Discovering their characteristics and effects on mobility and network performance in urban environments is a fundamental research task. In this paper, we firstly study the graph attributes of road networks by sampling real road networks in main cities of Europe and USA. We propose a new graph metric, called characteristic central length, in order to estimate the average shortest-path length of a large-scale spatial network. We find that real road networks from Europe and USA have different patterns with regard to some graph attributes and a simple grid model is inadequate to describe them. Considering the diverse patterns of urban road networks caused by obstacles and shortcuts, we propose a random road network model, called the GRE model. The model is validated through fitting it to real road network samples using a genetic algorithm and simulation of delay-tolerant networks. The simulation results have shown that by extending the grid model with new probabilistic parameters, the GRE model has better capability on approximating real road networks. The simulation results have also shown that delay-tolerant networks operating on road networks may have better performance than scenarios without road networks. [ABSTRACT FROM AUTHOR]

With the advent of wireless technologies such as Wi-Fi Direct and Near Field Communication (NFC), infrastructure-less Peer-to-Peer (P2P) content sharing among mobile devices is set to become more ubiquitous. Delay-Tolerant Networks (DTNs), with their opportunistic message forwarding strategy, can be leveraged to provide seamless connectivity in such scenarios. To the best of our knowledge, little has been done to understand the performance of DTNs under realistic settings involving the interplay of diverse factors such as bundle fragmentation, scheduling, and buffer spacing. In this paper, we look at Queueing Petri Nets (QPNs) as a modeling framework to study the performance of DTN routing. We develop QPN models for DTNs of increasing complexity in an incremental fashion, starting from a network that employs the rudimentary direct transmission routing protocol to a network that employs a family of multi-hop and replication-based routing protocols (namely \((p,q)\) -epidemic routing). The complete QPN model considers a number of realistic factors that impact performance such as finite buffer space, finite link bandwidth, bundles with different priorities and intra-scheduling delays arising due to different levels of the memory hierarchy at the nodes. We come up with a three-fold validation scheme to assert the veracity of our proposed models, via comparison of results obtained from simulations of the QPN vis-a-vis those obtained from direct simulation of the underlying DTN and experimental results obtained from a testbed of Android based devices that employ a mobility emulation scheme. We also show a case to exemplify the analytical capability of the QPN, by deriving the underlying reachability graph and constructing an equivalent stochastic jump process. We identify the stochastic process to be a Semi-Markov Process (SMP) and hence arrive at a closed form expression for the end-to-end delivery latency by computing the hitting time of the SMP. We find that the model accurately captures the behavior of a DTN in numerous realistic scenarios, showing the efficacy of QPNs as a suitable modeling framework for evaluating the DTN routing protocols. [ABSTRACT FROM AUTHOR]

This paper presents a novel multicopy routing protocol for disruption-tolerant networks whose objective is to minimize energy expended on communication. The protocol is designed for disaster-response applications, where power and infrastructure resources are disrupted. Unlike other delay-tolerant networks, energy is a vital resource in postdisaster scenarios to ensure availability of (disruption-tolerant) communication until infrastructure is restored. Our approach exploits naturally recurrent mobility and contact patterns in the network, formed by rescue workers, volunteers, survivors, and their (possibly stranded) vehicles to reduce the number of message copies needed to attain an adequate delivery ratio in the face of disconnection and intermittent connectivity. A new notion of intercontact routing is proposed that allows estimating route delays and delivery probabilities, identifying more reliable routes and controlling message replication and forwarding accordingly. In addition, we augment the protocol with a differentiated message delivery service that enables the network to function even in an extremely low energy condition. We simulate the scheme using a mobility model that reflects recurrence inspired by disaster scenarios and compare our results to previous DTN routing techniques. The evaluation shows that the new approach reduces the resource overhead per message over previous approaches while maintaining a comparable delivery ratio at the expense of a small (bounded) increase in latency. [ABSTRACT FROM AUTHOR]

This paper focuses on the problem of rostering in intermittently connected passive RFID networks. It aims to report a list of tagged mobile nodes that appear in given interested area(s) and time interval(s). Such rostering faces several unique challenges. First, the network consists of two dramatically different types of nodes: powerful static readers and extremely resource-constrained mobile tags. Communication can be established from a reader to a tag only, but not tags to tags or readers to readers. Therefore, the connectivity is very low and intermittent. Besides connectivity, the tag's computation power is also intermittent. It is available only for a short interval when the tag is powered up by a nearby reader, rendering any continuous functions impossible. Moreover, the capacity of tags is so limited that it becomes the critical network resource and communication bottleneck. To address the above challenges, we propose a rostering algorithm that employs a dynamic space-efficient coding scheme to construct hypothetic packet candidates, appraises their values according to information redundancy and tag mobility, and establishes a 0-1 Knapsack model to choose the best set of packets, which together maximize their total (redundancy-excluded) value, but do not exceed the capacity of a tag. We carry out experiments that involve 38 volunteers for nine days and perform large-scale simulations to evaluate the proposed rostering scheme. [ABSTRACT FROM AUTHOR]

In order to achieve data delivery in Delay Tolerant Networks (DTN), researchers have proposed the use of store-carry-and-forward protocols: a node there may store a message in its buffer and carry it along for long periods of time, until an appropriate forwarding opportunity arises. This way, messages can traverse disconnected parts of the network. Multiple message replicas are often propagated to further increase delivery probability. This combination of long-term storage and message replication imposes a high storage and bandwidth overhead. Thus, efficient scheduling and drop policies are necessary to 1) decide on the order by which messages should be replicated when contact durations are limited, and 2) which messages should be discarded when nodes' buffers operate close to their capacity. In this paper, we propose a practical and efficient joint scheduling and drop policy that can optimize different performance metrics, such as average delay and delivery probability. We first use the theory of encounter-based message dissemination to derive the optimal policy based on global knowledge about the network. Then, we introduce a method that estimates all necessary parameters using locally collected statistics. Based on this, we derive a distributed scheduling and drop policy that can approximate the performance of the optimal policy in practice. Using simulations based on synthetic and real mobility traces, we show that our optimal policy and its distributed variant outperform existing resource allocation schemes for DTNs. Finally, we study how sampled statistics can reduce the signaling overhead of our algorithm and examine its behavior under different congestion regimes. Our results suggest that close to optimal performance can be achieved even when nodes sample a small percentage of the available statistics. [ABSTRACT FROM PUBLISHER]

Delay/Disruption Tolerant Networks (DTNs) have been identified as one of the key areas in the field of wireless communication, wherein sparseness and delay are particularly high. They are emerging as a promising technology in vehicular, planetary/interplanetary, military/tactical, disaster response, underwater and satellite networks. DTNs are characterized by large end-to-end communication latency and the lack of end-to-end path from a source to its destination. These characteristics pose several challenges to the security of DTNs. Especially, Byzantine attacks in which one or more legitimate nodes have been compromised and fully controlled by the adversary can give serious damages to the network in terms of latency and data availability. Using reputation-based trust management systems is shown to be an effective way to handle the adversarial behavior in Mobile Ad hoc Networks (MANETs). However, because of the unique characteristics of DTNs, those traditional techniques do not apply to DTNs. Our main objective in this paper is to develop a robust trust mechanism and an efficient and low cost malicious node detection technique for DTNs. Inspired by our recent results on reputation management for online systems and e-commerce, we develop an iterative malicious node detection mechanism for DTNs referred as ITRM. The proposed scheme is a graph-based iterative algorithm motivated by the prior success of message passing techniques for decoding low-density parity-check codes over bipartite graphs. Applying ITRM to DTNs for various mobility models, we observed that the proposed iterative reputation management scheme is far more effective than well-known reputation management techniques such as the Bayesian framework and EigenTrust. Further, we concluded that the proposed scheme provides high data availability and packet-delivery ratio with low latency in DTNs under various adversary attacks which attempt to both undermine the trust and detection scheme and the packet delivery protocol. [ABSTRACT FROM PUBLISHER]

The increasing penetration of smart devices with networking capability form novel networks. Such networks, also referred as pocket switched networks (PSNs), are intermittently connected and represent a paradigm shift of forwarding data in an ad hoc manner. The social structure and interaction of users of such devices dictate the performance of routing protocols in PSNs. To that end, social information is an essential metric for designing forwarding algorithms for such types of networks. Previous methods relied on building and updating routing tables to cope with dynamic network conditions. On the downside, it has been shown that such approaches end up being cost ineffective due to the partial capture of the transient network behavior. A more promising approach would be to capture the intrinsic characteristics of such networks and utilize them in the design of routing algorithms. In this paper, we exploit two social and structural metrics, namely centrality and community, using real human mobility traces. The contributions of this paper are two-fold. First, we design and evaluate BUBBLE, a novel social-based forwarding algorithm, that utilizes the aforementioned metrics to enhance delivery performance. Second, we empirically show that BUBBLE can substantially improve forwarding performance compared to a number of previously proposed algorithms including the benchmarking history-based PROPHET algorithm, and social-based forwarding SimBet algorithm. [ABSTRACT FROM AUTHOR]

Disseminating shared information to many vehicles could incur significant access fees if it relies only on unicast cellular communications. We consider the problem of efficient content dissemination over a vehicular network, in which vehicles are equipped with two kinds of radios: a high-cost low-bandwidth, long-range cellular radio, and a free high-bandwidth short-range radio. We formulate and solve an optimization problem to maximize content dissemination from the infrastructure to vehicles within a predetermined deadline while minimizing the cost associated with communicating over the cellular connection. [ABSTRACT FROM PUBLISHER]

Human-associated delay-tolerant networks (HDTNs) are new networks where mobile devices are associated with humans and can be viewed from multiple dimensions including geographic and social aspects. The combination of these different dimensions enables us to comprehend delay-tolerant networks and consequently use this multidimensional information to improve overall network efficiency. Alongside the geographic dimension of the network, which is concerned with geographic topology of routing, social dimensions such as social characters can be used to guide the routing message to improve not only the routing efficiency for individual nodes, but also efficiency for the entire network. We propose a multidimensional routing protocol (M-Dimension) for the human-associated delay-tolerant networks which uses local information derived from multiple dimensions to identify a mobile node more accurately. The importance of each dimension has been measured by the weight function and it is used to calculate the best route. The greedy routing strategy is applied to select an intermediary node to forward message. We compare M-Dimension to the existing benchmark routing protocols via MIT reality Data Set and INFOCOM 2006 Data Set, which are real human-associated mobile network trace files. The results of our simulations show that M-Dimension significantly increases the average success ratio with a competitive end-to-end delay when compared with other multicast DTNs routing protocols. [ABSTRACT FROM AUTHOR]

In this work, we address the problem of Named Data Networking (NDN)-based fake content dissemination in Opportunistic Mobile Networks (OMNs), where nodes have intermittent connectivity and typically lack in end-to-end communication paths. It is important to mitigate the dissemination of such fake contents not only because they waste bandwidth for legitimate communication, but also because such files can be harmful for devices. However, the inherent characteristics of OMNs make such mitigation a challenging task. In this context, we consider a group of nodes, Fake Content Providers (FCPs), who, on receiving content requests, respond with fake contents, rather than the real version. In particular, we consider four different behaviors of the FCPs—referred to as threat scenarios—depending on whether or not they always respond to all requests with fake contents. We analyze these distinct threat scenarios, and characterize the relative performance degradation arising because of them. To mitigate the adverse effects of FCPs, we propose two schemes, wherein the identified FCPs are blacklisted permanently or temporarily, and communication with them is restricted. Results of simulation-based experiments using real-life connection traces show that, compared to the normal scenario with no FCP, the percentage of content requests satisfied decreases by 20–40 percent in the presence of 40 percent FCPs in the OMN. Moreover, in the same scenario, the average latency of content satisfaction relatively increases by up to 176 percent with respect to the normal scenario. However, on using the proposed mitigation schemes, the latency can be reduced by about 13–36 percent together with up to 9 percent improvement in the number of interests satisfied. [ABSTRACT FROM AUTHOR]

Today’s modern communication technologies such as cloud radio access and software defined networks are key candidate technologies for enabling 5G networks as they incorporate intelligence for data-driven networks. Traditional content caching in the last mile access point has shown a reduction in the core network traffic. However, the radio access network still does not fully leverage such solution. Transmitting duplicate copies of contents to mobile users consumes valuable radio spectrum resources and unnecessary base station energy. To overcome these challenges, we propose huMan mObility-based cOntent Distribution (MOOD) system. MOOD exploits urban scale users’ mobility to allocate radio resources spatially and temporally for content delivery. Our approach uses the broadcast nature of wireless communication to reduce the number of duplicated transmissions of contents in the radio access network for conserving radio resources and energy. Furthermore, a human activity model is presented and statistically analyzed for simulating people daily routines. The proposed approach is evaluated via simulations and compared with a generic broadcast strategy in an actual existing deployment of base stations as well as a smaller cells environment, which is a trending deployment strategy in future 5G networks. MOOD achieves 15.2 and 25.4 percent of performance improvement in the actual and small-cell deployment, respectively. [ABSTRACT FROM AUTHOR]

In some specific applicable scenarios, nodes are placed in some geographical areas and limited to move in their own community. We investigate the tradeoff between the delivery delay and the number of transmissions in the above multi-community delay tolerant networks by propagating a data packet in a carefully chosen segment of community. First, three restricted epidemic routings are proposed: the shortest community-hop path scheme, the rectangle scheme, and the parallelogram scheme. Second, the ratios of the average number of communities that can propagate the data packet in the proposed schemes to those that can propagate in the epidemic routing are analyzed. The ratios are found to be small and to decrease with the increase in the number of communities. The tail distribution of the inter-meeting time of any two nodes in the neighboring communities is then demonstrated to be exponential. Third, the delivery delay of the proposed schemes is analyzed by Markovian chain tool. The experiments show that the theoretical model proposed here is reliable, and that the proposed schemes can significantly decrease the number of transmissions, even if these schemes increase the delivery delay to some extent. [ABSTRACT FROM AUTHOR]

We consider a delay tolerant network under two message forwarding schemes—a non-replicative direct delivery scheme and a replicative epidemic routing scheme. Our objective is to track the degree of spread of a message in the network. Such estimation can be used for on-line control of message dissemination. With a homogeneous mobility model with pairwise i.i.d. exponential inter-meeting times, we rigorously derive the system dynamic and measurement equations for optimal tracking by a Kalman filter. Moreover, we provide a framework for tracking a large class of processes that can be modeled as density-dependent Markov chains. We also apply the same filter with a heterogeneous mobility, where the aggregate inter-meeting times exhibit a power law with exponential tail as in real-world mobility traces, and show that the performance of the filter is comparable to that with homogeneous mobility. Through customized simulations, we demonstrate the trade-offs and provide several insightful observations on how the number of observers impacts the filter performance. [ABSTRACT FROM AUTHOR]

We propose an algorithm for maximizing the lifetime of a wireless sensor network when there is a mobile sink and the underlying application can tolerate some amount of delay in delivering the data to the sink. The algorithm is distributed, and in addition, mostly uses local information. Such an algorithm can be implemented by parallel and/or distributed execution and the overhead of message passing is low. It is also possible to embed the algorithm into a network protocol so that the sensor nodes and the sink can run it directly as part of the network operation. We give a proof of the algorithm's optimality and the boundedness of the queue sizes, both in the long-run average sense. The proof is based on analyzing a Lyapunov drift. [ABSTRACT FROM AUTHOR]

Cooperative packet delivery can improve the data delivery performance in wireless networks by exploiting the mobility of the nodes, especially in networks with intermittent connectivity, high delay and error rates such as wireless mobile delay-tolerant networks (DTNs). For such a network, we study the problem of rational coalition formation among mobile nodes to cooperatively deliver packets to other mobile nodes in a coalition. Such coalitions are formed by mobile nodes which can be either well behaved or misbehaving in the sense that the well-behaved nodes always help each other for packet delivery, while the misbehaving nodes act selfishly and may not help the other nodes. A Bayesian coalitional game model is developed to analyze the behavior of mobile nodes in coalition formation in presence of this uncertainty of node behavior (i.e., type). Given the beliefs about the other mobile nodes' types, each mobile node makes a decision to form a coalition, and thus the coalitions in the network vary dynamically. A solution concept called Nash-stability is considered to find a stable coalitional structure in this coalitional game with incomplete information. We present a distributed algorithm and a discrete-time Markov chain (DTMC) model to find the Nash-stable coalitional structures. We also consider another solution concept, namely, the Bayesian core, which guarantees that no mobile node has an incentive to leave the grand coalition. The Bayesian game model is extended to a dynamic game model for which we propose a method for each mobile node to update its beliefs about other mobile nodes' types when the coalitional game is played repeatedly. The performance evaluation results show that, for this dynamic Bayesian coalitional game, a Nash-stable coalitional structure is obtained in each subgame. Also, the actual payoff of each mobile node is close to that when all the information is completely known. In addition, the payoffs of the mobile nodes will be at least as high as those when they act alone (i.e., the mobile nodes do not form coalitions). [ABSTRACT FROM PUBLISHER]

The movement of real users often follows patterns that can be characterized by certain statistical metrics of the contacts. Such metrics are useful for routing decisions, especially in sparse mobile ad hoc networks where node connectivity is opportunistic and messages are delivered using store-carry-forward routing. Past analysis on real-world data traces indicates that human behaviors affect the node contact pattern and spatial dependency exists among mobile nodes. A new metric called the expected dependent delay that characterizes the expected delay of a contact dependent on the previous hop is proposed. It characterizes the spatial dependency between neighboring contact pairs and reflects the regularity in node movement. In sparse opportunistic mobile ad hoc networks, a good approximation of the expected delay of a multihop path can be derived as the sum of the expected delay of the first hop and the expected dependent delays of later hops. We apply the proposed path-delay estimation to end-to-end routing. Simulation results show that compared with routing schemes that consider only the delivery probability or the expected delay, the proposed scheme can reduce the message delay significantly, when the network is sufficiently sparse and the spatial dependency is quantitatively constant over time. Moreover, the proposed method is tractable and can be easily implemented in combination with other routing techniques such as multipath routing and per-contact routing. [ABSTRACT FROM AUTHOR]