Mobile Opportunistic Networks Research Articles

A Socially Aware Routing Protocol in Mobile Opportunistic Networks

A Socially Aware Routing Protocol in Mobile Opportunistic Networks

Evaluating the impact of network loads and message size on mobile opportunistic networks in challenged environments

The use of mobile opportunistic networks may help users to gain access to an available network connection for communication in challenged environments. For instance, areas that lack an available infrastructure for communication (e.g., rural or sparse areas) or areas with an infrastructure where the network connection is not as accessible (e.g., restricted/full of interference access networks or a high cost roaming zone). In this paper, we observe how the overall network performs with the changes of network load (e.g., number of messages) along with the long-sized messages in such environments. With real-world trace-driven simulations, we compare and contrast the impact of the message generation rates and the message size in different opportunistic routing protocols in a challenged environment to see this performance impact. Our experimental results show that in such environments, mobile opportunistic networks improve the overall message delivery performance using user's interactions and social collaborations even with higher message generation rates and increased message sizes.

Maximum data delivery probability-oriented routing protocol in opportunistic mobile networks

Some recent studies utilize node contact patterns to aid the design of routing protocol in Opportunistic Mobile Networks (OppNets). However, most existing studies only utilize one hop contact information to design routing protocol. In order to fully utilize nodes’ collected contact information to improve the performance of data forwarding, in this paper we focus on exploiting node contact patterns from the multi-hop perspective. We first give the definition of opportunistic forwarding path, and propose a model to calculate the maximum data delivery probability along different opportunistic forwarding paths. Second, based on the maximum data delivery probability, we propose a novel approach to improve the performance of data forwarding in OppNets based on two forwarding metric. The proposed forwarding strategy first manages to forward data copies to nodes have higher centrality value at the global scope. Afterwards, maximum data delivery probability to the destination is evaluated, to ensure that data is carried and forwarded by relays with higher capability of contacting the destination. Finally, extensive real trace-driven simulations are conducted to compare the proposed routing protocol with other existing routing protocols in terms of delivery ratio and delivery cost. The simulation results show that our proposed routing protocol is close to Epidemic Routing in terms of delivery ratio but with significantly reduced delivery cost. Additionally, our proposed routing protocol outperforms Bubble Rap and Prophet in terms of delivery ratio, and the delivery cost of our proposed routing protocol is very close to that of Bubble Rap.

Named Content Searching in Opportunistic Mobile Networks

In this letter, we study the adaptation of named data networking-based named content searching in opportunistic mobile networks (OMNs). Given the inherent uncertainty in OMNs, our goal is to replicate the content requests to a suitable set of nodes that can help improve users’ experience in terms of requests satisfaction and latency. To this end, we propose a scheme, content searching as regret minimization (CHARM), based on the technique of random regret minimization. In CHARM, content interest replication and non-replication choices are expressed in terms of several measurable attributes. Regrets associated with the two choices indicate whether or not an interest should be replicated. Moreover, to reduce overhead, CHARM uses dynamic time-to-live adaptation, where the lifetime of a message is proactively scaled down. The results of performance evaluation based on real-life traces and synthetic mobility model indicate that CHARM can improve the number of interests satisfied and latency, respectively, by up to 1.6 and 1.4 times when compared with a contemporary scheme.

SNVC: Social networks for vehicular certification

Vehicular Disruption Tolerant Networks appear due to the search of information by drivers, which are organized into mobile ad hoc networks that may suffer from long interruptions. In such networks, both humans as well as machines contribute with information about the traffic and road conditions. As humans can be biased or may be compelled to disseminate false information for personal gains, the network should incorporate mechanisms to assert the trust and reputation of the information sources. This article proposes an inter-vehicle certification mechanism based on social networks to enable reliable exchange of messages called SNVC - Social Networks for Vehicular Certification. It enables mobile devices to share keys through direct contacts between two acquaintances that warrant their identity, so they mutually sign their certificates, establishing trust in the cyber-physical system. Certificates signed by the friend of a user can be validated if the public key of this friend is validated by a friend in common in the social network. Further, a reputation system rates users or devices based on the reliability of the information that they produce. The evaluation of the mechanism shows the behavior of vehicular networks using real mobility traces. The results show the feasibility of the trust in friends as a way to improve the exchange of reliable messages in a Mobile Opportunistic Network. Also, the attribution of reputation for reliable information promotes the recognition of trustworthy users.

A Social Motivation-aware Mobility Model for Mobile Opportunistic Networks

In mobile opportunistic networks (MONs), human-carried mobile devices such as PDAs and smartphones, with the capability of short range wireless communications, could form various intermittent contacts due to the mobility of humans, and then could use the contact opportunity to communicate with each other. The dynamic changes of the network topology are closely related to the human mobility patterns. In this paper, we propose a social motivation-aware mobility model for MONs, which explains the basic laws of human mobility from the psychological point of view. We analyze and model social motivations of human mobility mainly in terms of expectancy value theory and affiliation motivation. Furthermore, we introduce a new concept of geographic functional cells, which not only incorporates the influence of geographical constraints on human mobility but also simplifies the complicated configuration of simulation areas. Lastly, we validate our model by simulating three real scenarios and comparing it with reality traces and other synthetic traces. The simulation results show that our model has a better match in the performance evaluation when applying social-based forwarding protocols like BUBBULE.

Souk: Spatial Observation of Human Kinetics

Simulating human-centered pervasive systems requires accurate assumptions on the behavior of human groups. Recent models consider this behavior as a combination of both social and spatial factors. Yet, establishing accurate traces of human groups is difficult: current techniques capture either positions, or contacts, with a limited accuracy.In this paper we introduce a new technique to capture such behaviors. The interest of this approach lies in the unprecedented accuracy at which both positions and orientations of humans, even gathered in a crowd, are captured. The open-source software pipeline we developed to exploit captured data allows extraction of several metrics on movement and social contacts, and permits study of their respective interrelationship. From the mobility to the topological connectivity, this framework offers a layered approach that can be tailored, allowing to compare and reason about models and traces.We demonstrate the accuracy and validity of our approach on social events and calibration runs in which we captured the motions of humans. In particular, we introduce an open-access trace of 50 individuals and compare it against random waypoint models that have the same global characteristics. Our fine-grain analyses, that take into account social interactions between users, show that the random way point model does not provide accurate predictions for socially-induced motion; to model human kinetics, new group- and interaction-based models should be developed. From the computer science point of view, these models are required to fully exploit the power of human-centered mobile computing, crucial for ubiquitous computing, and referred to as Short Range Communication Systems, Mobile Opportunistic Networking, or Mobile Networking in Proximity.

Analytical evaluation of the performance of contact-Based messaging applications

Communications in mobile opportunistic networks, instead of using the Internet infrastructure, take place upon the establishment of ephemeral contacts among mobile nodes using direct communication. In this paper, we analytically model the performance of mobile opportunistic networks for contact-based messaging applications in city squares or gathering points, a key challenging topic that is required for the effective design of novel services. We take into account several social aspects such as: the density of people, the dynamic of people arriving and leaving a place, the size of the messages and the duration of the contacts. We base our models on Population Processes, an approach commonly used to represent the dynamics of biological populations. We study their stable equilibrium points and obtain analytical expressions for their resolution.The evaluations performed show that these models can reproduce the dynamics of message diffusion applications. We demonstrate that when the density of people increases, the effectiveness of the diffusion is improved. Regarding the arrival and departure of people, their impact is more relevant when the density of people is low. Finally, we prove that for large message sizes the effectiveness of the epidemic diffusion is reduced, and novel diffusion protocols should be considered.

Contact duration aware cache refreshing for mobile opportunistic networks

Caching is a practical data access approach in mobile opportunistic networks, which enables mobile terminals to obtain data from adjacent nodes and to reduces accessing latency, whereby the updating files should be delivered to the caching nodes on time when the source is refreshed in order to maintain the freshness of the cached data. Due to the node mobility and short communication range, the contact duration in mobile opportunistic networks is short and this limits the amount of data transmitted in one contact. However, current cache refreshing schemes often ignore this critical issue. In this study, the authors study the contact duration aware cache refreshing in mobile opportunistic networks. Specifically, they establish a two-state Markov chain to describe the data delivered from one node to another. Based on the proposed model, they investigate a tree structure to refresh the cached data, where each node is responsible to refresh the data cached at its children and it may opportunistically rely on some relays outside the tree to improve the refreshing efficiency. Extensive trace-driven simulations validate the effectiveness of the authors’ scheme in terms of improving cache refreshing in challenging mobile environments.

OPPO: An optimal copy allocation scheme in mobile opportunistic networks

Mobile Opportunistic Networks (MONs) use the store-carry-and-forward scheme to transmit packets, so as to deal with the intermittently connected links. This new communication paradigm makes them very different from the traditional multi-hop wireless networks. To improve the delivery performance, some smart forwarding schemes have been proposed by injecting multiple copies of packets into the temporal network. Unfortunately, these schemes allocate data copies following the aggregate contact information, i.e., information obtained by considering the samples from all pairs. They ignore the individual contact feature of nodes. We show that the aggregate contact can be very different from the contact of individual pairs, therefore, using the former to guide copy allocation is not correct in general, although it works well in some cases. In this paper, we propose OPPO, an optimal copy allocation scheme in MONs. OPPO exploits the transient contact ratio of nodes to spray data copies. Theoretical analysis proves that OPPO achieves the optimal delivery delay, and experimental results verify it simultaneously improves the packet delivery ratio compared to the SprayWait and HS, two state-of-the-art works.

Search in digital pockets: retrieving remote content in mobile opportunistic networks

Due to the fierce competition for the wireless spectrum, operators have recently focused on short-range communications, which promises higher spectral efficiency, lower energy consumption, and less strain on the operators’ core networks. Mobile opportunistic communications, that is, short-range communications without any network assistance, is of considerable practical value since it entails almost no monetary cost and does not rely on any infrastructure. Compared to the extensive work on opportunistic networks, the predominance of video and other content calls for new content-centric approaches. To this end, the motivation of this article is to explain how opportunistic search can discover the content stored in remote mobile devices and deliver it to the requesting node. We abstract the problem domain as three layers, network topology, content, and query; and describe the interactions among these components. After reviewing each layer, we introduce several schemes for content availability estimation that do not rely on any information exchange but simply use already available information. Additionally, we highlight some open research directions.

Energy Efficiency and Contact Opportunities Tradeoff in Opportunistic Mobile Networks

To discover neighbor nodes, nodes in opportunistic mobile networks (OppNets) have to probe their environment continuously. This can be an extremely energy-consuming process. If nodes probe very frequently, a lot of energy will be consumed in the contact probing process and might be inefficient. On the other hand, infrequent contact probing might cause nodes to miss many of their contacts. Therefore, there exists a tradeoff between energy efficiency and contact opportunities in OppNets. To investigate this tradeoff, we first propose a model to investigate the contact probing process based on the random-waypoint model and obtain the expressions of the single detecting probability and the double detecting probability. Moreover, we also demonstrate that among all contact probing strategies with the same average probing interval, which do not have preknowledge of the contact process, the strategy that probes at a constant interval performs better than any arbitrary probing strategy in expectation in the single contact probing process. Then, extensive simulations are conducted to validate the correctness of our proposed model. Finally, based on the proposed model, we analyze the tradeoff between energy efficiency and the total number of effective contacts in the single and double contact probing processes. Our results show that the total number of effective contacts in the single and double contact probing processes has a lower bound and an upper bound, and the good tradeoff points are obviously different when the speed of nodes is different.

New approaches for characterizing inter-contact times in opportunistic networks

Characterizing the contacts between nodes is of utmost importance when evaluating mobile opportunistic networks. The most common characterization of inter-contact times is based on the study of the aggregate distribution of contacts between individual pairs of nodes, assuming an homogenous network, where contact patterns between nodes are similar. The problem with this aggregate distribution is that it is not always representative of the individual pair distributions, especially in the short term and when the number of nodes in the network is high. Thus, deriving results from this characterization can lead to inaccurate performance evaluation results.In this paper, we propose new approaches to characterize the inter-contact times distribution having a higher representativeness and, thus, increasing the accuracy of the derived performance results. Furthermore, these new characterizations require only a moderate number of contacts in order to be representative, thereby allowing to perform a temporal modelization of traffic traces. This a key issue for increasing accuracy, since real-traces can have a high variability in terms of contact patterns along time. The experiments show that the new characterizations, compared with the established one, are more precise, even using short time contact traces.

Utility-Based Exploration for Performance Enhancement in Opportunistic Mobile Networks

Opportunistic mobile networks (OMNs), which are formed by mobile devices carried by human users, present an interesting communication paradigm in the absence of access to global network connectivity or any form of network infrastructure. In this work, we combine the natural mobility of the human users—which has been shown to resemble Levy Walk—in OMNs, together with intentional explorations . We consider the case where the human users in an OMN undergo explorations, i.e., occasionally visit a set of fixed point of interests (PoI), for example, shopping malls. The objective of this work is two-fold-1) Establishing that limited explorations of the users can help in enhancing the performance of OMNs, and 2) Formulating a method to decide whether or not a user should undergo exploration. In this regard, we propose two schemes based on prospect theory (PT) and expected utility theory (EUT). The results of extensive simulation-based performance evaluation indicate that limited exploration can promote the delivery ratio of messages by large levels—about $7$ - $33$ percent depending on the number of randomly placed PoI, and about $36$ percent depending upon the terrain size. Moreover, the time spent in exploration, on an average, is negligibly small—a typical value is about $0.55$ percent of the simulation duration, which indicates its feasibility in real life.

Mobile crowdsourcing in peer-to-peer opportunistic networks: Energy usage and response analysis

With the popularity of mobile social networking and the emergence of ideas such as participatory sensing, mobile crowdsourcing has the potential to help tackle new problems in relation to real-time data collection and coordination among a large number of participants. Due to the unreliability and dynamic behavior of mobile opportunistic networks, there are several key issues concerning the development of crowdsourcing-related mobile applications that need to be considered. In this paper, we investigate task propagation models devised to support mobile crowdsourcing in intermittently connected opportunistic networks. The propagation strategy is used to disseminate tasks among a crowd of peers. We investigate response models (i.e., to estimate the number of responses to expect in the network) and energy consumption models (for estimating the energy used by both a task-originator and workers) and study their behavior under different conditions in comprehensive simulations. The findings will show the interplay and relationships between mobile crowdsourcing factors and the number of peers responding and energy consumption.

A novel approach for inhibiting misinformation propagation in human mobile opportunistic networks

Mobile Opportunistic Networks (MONs) are effective solutions to uphold communications in the situations where traditional communication networks are unavailable. In MONs, messages can be disseminated among mobile nodes in an epidemic and delay-tolerant manner. However, MONs can be abused to disseminate misinformation causing undesirable effects in the general public, such as panic and misunderstanding. To deal with this issue, we first propose a formal model to formulate the process of misinformation propagation in MONs, considering human psychological behaviors. Secondly, we explore a general framework to describe the random node mobility, and derive a new contact rate between nodes, which is closely related to mobility properties of nodes. Thirdly, we propose a novel approach based on vaccination and treatment strategies for inhibiting misinformation propagation in human MONs. Moreover, a novel pulse control model of misinformation propagation is developed. Finally, through the derivation and stability analysis of a misinformation-free period solution of the proposed model, we obtain a threshold upon which misinformation dies out in a human MON. The extensive simulation results validate our theoretical analysis.

The Potential of Mobile Opportunistic Networks for Data Disseminations

Mobile opportunistic networks make use of node mobility to provide occasional contact opportunities for mobile devices to deliver data. In this paper, we investigate the inherent properties of data disseminations in mobile opportunistic networks by answering the question regarding how far and how fast a packet can be disseminated in mobile opportunistic networks. This problem has been overlooked by recent research, but it is very important because it reveals the potential for mobile opportunistic networks to support emerging applications such as mobile commerce and emergency services that may involve time and location sensitive information dissemination. Our investigations are taken from the perspectives of small and large scales. From the perspective of small scale, the probability distributions of the minimum time needed by the data to spread to a given region, namely, T, are deduced for both the one-copy case and the multiple-copy case. From the perspective of large scale, by using the large deviation theory, the probability distributions of T are deduced for both the one-copy case and the multiple-copy case when the destination region is far enough from the data origin.

Exploiting Heterogeneity for Improving Forwarding Performance in Mobile Opportunistic Networks: An Analytic Approach

Heterogeneity arises in a wide range of scenarios in mobile opportunistic networks and is one of the key factors that govern the performance of forwarding algorithms. While the heterogeneity has been empirically investigated and exploited in the design of new forwarding algorithms, it has been typically ignored or marginalized when it comes to rigorous performance analysis of such algorithms. In this paper, we develop an analytical framework to quantify the performance gain achievable by exploiting the heterogeneity in mobile nodes' contact dynamics. In particular, we derive a delay upper bound of a heterogeneity-aware static forwarding policy per each given number of message copies and obtain its closed-form expression, which enables our quantitative study on the benefit of leveraging underlying heterogeneity structure in the design of forwarding algorithms. In addition, we develop a dynamic forwarding policy that performs as an extension of the static forwarding policy while proven to improve the delay performance. We then demonstrate that only a small fraction of total (unlimited) message copies, via both static and dynamic forwarding policies, are enough under various heterogeneous network settings to achieve the same delay as that obtained using the unlimited message copies when the networks become homogeneous. We also show that, given the same number of message copies, our dynamic forwarding policy significantly outperforms the `homogeneous-optimal' forwarding policy (up to about 50 percent improvement in the delay performance), especially when the number of message copies allowed in the networks is small.

Fundamental Analysis on Data Dissemination in Mobile Opportunistic Networks with Lévy Mobility

Mobile opportunistic networks take advantage of contact opportunities due to the mobility of individual nodes for distributing data. Studying the inherent traits of data dissemination in mobile opportunistic networks can reveal their potential to support emerging applications, such as emergency services and mobile commerce. In this paper, we employ the Levy mobility model to characterize the movement pattern of nodes. Because the Levy mobility closely mimics human walking patterns, the analysis model that we adopt is realistic. Our analyses consider small- and large-scale perspectives. In the small-scale case, we investigate the distribution of the minimum time needed by the data to spread to a given region. In the large-scale case, we examine the probability bounds of the earliest time at which the data arrives in a region that is sufficiently far away. We also derive the rate at which such a probability tends to zero as the distance to the region increases to infinity. The results of extensive numerical simulations validate our analysis.

Up-and-Down Routing through Nested Core-periphery Hierarchy in Mobile Opportunistic Social Networks

Routings in mobile opportunistic social networks (MOSNs) are challenging problems due to their dynamic network structures. This paper finds that MOSNs exhibit a nested core-periphery hierarchy (NCPH). In the NCPH, few active nodes with large weighted degrees are the network core, while the network peripheries are composed of inactive nodes with small weighted degrees. “Nested” indicates that the NCPH is preserved when periphery nodes are iteratively removed. A distributed labeling scheme is proposed to determine the NCPH with a granularity control. Based on the NCPH, this paper proposes an up-and-down routing protocol for MOSNs, which includes an upload phase and a download phase. A message can be uploaded from the source to the network core by iteratively forwarding the message to a relay that has a higher position in the NCPH. Then, space-efficient Bloom-filter-based routing hints are introduced to download messages from the network core to the destination. Compared to traditional hierarchical routings, the up-and-down routing protocol achieves a better balance among the data delivery delay, ratio, and cost. Extensive experiments demonstrate that the proposed routing protocol achieves a competitive performance on the data delivery delay and ratio, with a small cost on the prior information maintenance and a low forwarding cost.