Opportunistic Wireless Networks Research Articles

Markov Chain-based Mobility Prediction and Relay-node Selection for QoS Provisioned Routing in Opportunistic Wireless Network

In the fields of networking and communication, wireless sensor networks are a commonly used technology. Although Mobility in Wireless Networks or Mobile Ad hoc Networks (MANETs) were developed to solve most critical problems in a disaster scenario. However, data transmission in a disaster area is a difficult operation due to irregular connections between sensing devices and the sink. Opportunistic network-based MANETs are utilized to overcome this problem. There are many routing issues such as communication overhead ratio, packet loss, and packet delivery ratio at mobile nodes. There are several traditional approaches used in opportunistic networks for node localization and routing. The drawback of these traditional routing methods is their poor reliability. A Markov chain-based opportunistic routing protocol is proposed in this paper. A Markov chain model is used to predict the node mobility for the random mobility model, and a neighbor table-based relay node selection procedure is proposed. A Markov prediction model uses the history of a node’s movement without requiring additional information. By analyzing simulation metrics including delay, overhead rate, packet drop, and packet delivery rate, the proposed routing protocol is evaluated and verified based on the Packet Delivery Ratio (PDR) in an opportunistic network environment (ONE) simulator. In addition, existing routing protocols such as Spray and Wait (SNW), Epidemic, Prophet, and MaxPro differ from the proposed routing protocol in terms of buffer size, node count, and message generation rate. Corresponding result analysis demonstrates the superior performance of the proposed routing protocol over existing protocols.

UAV Charging Station Placement in Opportunistic Networks

Unmanned aerial vehicles (UAVs) are now extensively used in a wide variety of applications, including a key role within opportunistic wireless networks. These types of opportunistic networks are considered well suited for infrastructure-less areas, or urban areas with overloaded cellular networks. For these networks, UAVs are envisioned to complement and support opportunistic network performance; however, the short battery life of commercial UAVs and their need for frequent charging can limit their utility. This paper addresses the challenge of charging station placement in a UAV-aided opportunistic network. We implemented three clustering approaches, namely, K-means, Density-Based Spatial Clustering of Applications with Noise (DBSCAN), and random clustering, with each clustering approach being examined in combination with Epidemic, Spray and Wait, and State-Based Campus Routing (SCR) routing protocols. The simulation results show that determining the charging station locations using K-means clustering with three clusters showed lower message delay and higher success rate than deciding the charging station location either randomly or using DBSCAN regardless of the routing strategy employed between nodes.

Realistic Human Mobility Model for Opportunistic Networks

Within the opportunistic wireless network research community, the evaluation of a new network protocol depends almost entirely on simulation. Using simulation enables a researcher to test a wide variety of scenarios at a low cost compared to using a real system. In opportunistic networks, the mobil

Forwarding in Opportunistic Information-Centric Networks: An Optimal Stopping Approach

By natively supporting in-network caching and name-based forwarding, ICN brings in features that are relevant to better support data transmission in opportunistic wireless networks. Such environments are highly challenged because of the node mobility and intermittent contacts. Therefore, forwarding packets to the right node at the right moment is critical to data retrieval performance. This article proposes a novel ICN forwarding strategy that leverages notable metrics, such as centrality and reliability, and the optimal stopping theory to statistically select the best next-hop forwarders and the time to perform the forwarding decision. Simulations with realistic mobility traces show that the proposed forwarding strategy outperforms other state-of-the-art solutions by guaranteeing shorter retrieval time and less overhead in terms of packet replicas.

Efficient coding for unicast flows in opportunistic wireless networks

In this study the authors consider the scenario of multiple unicast flows intersecting a common router in an opportunistic wireless network. Instead of forwarding packets in each of the flows independently, the router can perform inter-session network coding and transmit codewords to improve the network throughput. Unlike coding for multicast data flow for which an optimal code can be constructed in polynomial time, coding for unicast data flows is a more complicated coding problem and has been shown to be an NP-hard problem. Opportunities for inter-session network coding have also been shown to exist in single-hop wireless data dissemination network such as Wi-Fi and WiMAX networks. In this study the authors propose an efficient coding scheme for unicast flows and demonstrate its higher coding gain over previously proposed state-of-the-art coding schemes, validated using simulation results and wireless sensor network testbed packet reception traces. The authors also show that the proposed algorithm is optimal for all 238 non-isomorphic coding instances for instances for n ≤ 4, and for 9500 of the 9608 non-isomorphic coding instances for n = 5, where n is the number of unicast packets.

Data collection with probabilistic guarantees in opportunistic wireless networks

Data collection with probabilistic guarantees in opportunistic wireless networks

Cluster based architecture and network maintenance protocol for medical priority aware cognitive radio based hospital.

Due to the rapid growth of wireless medical devices in near future, wireless healthcare services may face some inescapable issue such as medical spectrum scarcity, electromagnetic interference (EMI), bandwidth constraint, security and finally medical data communication model. To mitigate these issues, cognitive radio (CR) or opportunistic radio network enabled wireless technology is suitable for the upcoming wireless healthcare system. The up-to-date research on CR based healthcare has exposed some developments on EMI and spectrum problems. However, the investigation recommendation on system design and network model for CR enabled hospital is rare. Thus, this research designs a hierarchy based hybrid network architecture and network maintenance protocols for previously proposed CR hospital system, known as CogMed. In the previous study, the detail architecture of CogMed and its maintenance protocols were not present. The proposed architecture includes clustering concepts for cognitive base stations and non-medical devices. Two cluster head (CH selector equations are formulated based on priority of location, device, mobility rate of devices and number of accessible channels. In order to maintain the integrity of the proposed network model, node joining and node leaving protocols are also proposed. Finally, the simulation results show that the proposed network maintenance time is very low for emergency medical devices (average maintenance period 9.5 ms) and the re-clustering effects for different mobility enabled non-medical devices are also balanced.

Cryptographic Approach of Generic Caching strategy for Opportunistic Wireless Networks (OPPNETS)

In Opportunistic networks, if a mobile finds that the content of its interest is available in other mobiles, it will send a message to request for the content and download it. The term subscriber denotes a node which requests for the content and the term publisher denotes a node which has the content. There can be two types of caches in a mobile node, namely private and public caches. Private cache stores the data of its own interest where as public cache stores the data of other nodes' interests. While a subscriber node requests another node for a particular content that is in the communication range for which it is missing, thereafter it forwards the request to other neighbouring nodes. In the case of public cache, there may be an intruder who issues false requests on behalf of a subscriber thereafter may get the access of the publisher's device and tries to keep the device busy always and unavailable. Thus it achieves the denial of service (DOS) attack. In this paper I investigate the various attacks that aim to degrade the public caching capabilities and propose a special kind of caching scheme called a Signature Generic Cache which stores the public data contents with the digital signature. Here digital signature is formed by taking the hash of the data content and then encrypting the data one by one with the publisher's private key whose purpose is to guarantee the integrity of the cached content. In one-way authentication, the publisher assures that the request is from the trusted user by validating the requester's digital certificate and thus it avoids security vulnerabilities. In order to conduct my study, I evaluate the performance of Signature generic caching scheme by using OMNET++ simulator. In this paper, I present the results by adopting the latest version of INET framework to implement the concept of Oppnets and NETA framework in order to show the various network attacks which are built on the top of OMNET++.

Data Collection with Probabilistic Guarantees in Opportunistic Wireless Networks

Sensors can be embedded in many mobile devices/objects such as smart phones, vehicles and animals to collect data from the surrounding environment. These mobile devices can communicate with each other by wireless techniques to form opportunistic wireless networks (OWNs). OWNs have volatile network topology and loose connectivity. Data collection from mobile devices is very challenging. This paper proposes a data collection protocol named DCPG with probabilistic guarantees in OWNs. DCPG consists of four parts: broadcasting sink's position periodically, electing collectors by partitioning a network into grids, direct transmission from general nodes to collectors, and directional transmission from collectors to the sink. The theoretical analysis shows that DCPG can adjust the parameters to guarantee that the average data collection ratio is greater than the user-specified data collection ratio. The simulation results show that DCPG outperforms the existing best protocol SMITE on the aspects of data collection ratio and communication overhead.

How to be an efficient asynchronous neighbourhood discovery protocol in opportunistic cognitive wireless networks

In opportunistic cognitive radio networks CRNs there is a need of on-demand searching for a control traffic channel by cognitive radio CR users in order to be able to initiate a communication. The neighbourhood discovery ND phase is challenging due to the dynamics of such networks. Lately, there has been a proliferation of different RDV protocols. However, most protocols have a narrow focus, which is usually a RDV guarantee in a single cycle. Very rarely asynchronism is exploited as a main factor, or considering channel heterogeneity in terms of quality. In this study we show how to add and benefit from an asynchronous RDV extension and its enhancement. Thanks to induced asynchronism, the ranking of channels is introduced, allowing nodes to stay longer on better quality channels. We analyse the behaviour of different selected ND protocols in terms of time-to-rendezvous and normalised RDV. We show that an asynchronism significantly improves the efficiency of the studied protocols.

Opportunistic wireless network coding with relay node selection

Broadcasting nature of wireless communications makes it possible to apply opportunistic network coding (OPNC) by overhearing transmitted packets from a source to sink nodes. However, it is difficult to apply network coding to the topology of multiple relay and sink nodes. We propose to use relay node selection, which finds a proper node for network coding since the OPNC alone in the topology of multiple relays and sink nodes cannot guarantee network coding gain. The proposed system is a novel combination of wireless network coding and relay selection. In this paper, with the consideration of channel state and potential network coding gain, we propose several relay node selection techniques that have performance gain over the conventional OPNC and the conventional channel-based selection algorithm in terms of average system throughput.

FENC: Fast and Efficient Opportunistic Network Coding in wireless networks

Network coding is a newly developed technology that can cause considerable improvements in network throughput. COPE is the first network coding approach for wireless mesh networks and it is based on opportunistic Wireless Network Coding (WNC). It significantly improves throughput of multi-hop wireless networks utilizing network coding and broadcast features of wireless medium. In this paper we propose a new method, called FENC, for opportunistic WNC that improves the network throughput. In addition, its complexity is lower than other opportunistic WNC approaches. FENC utilizes division and conquer method to find an optimal network coding. The numerical results show that the proposed opportunistic algorithm improves the overall throughput as well as network coding approach.

Call admission control with active link protection for opportunistic wireless networks

In this paper we suggest a call admission control (CAC) algorithm for high speed downlink packet access HSDPA UMTS systems. In this algorithm the user requesting admission is gradually admitted into the system. This is done by setting a back-off factor limiting the new user's throughput. The back-off factor is gradually decreased leading to a gradual increase in the new user's throughput until it is fully integrated into the system. The back-off factor works on protecting the active links in a way that their rates do not drop below a guaranteed quality of service (QoS) level.