MinHop (MH) Transmission strategy to optimized performance of epidemic routing protocol

Delay tolerant network aims to provide the network architecture in environments where end-to-end path may never exist for long duration of time Furthermore dynamic topology changes limited buffer space and non stable connectivity make routing a challenging issue The research contribution regarding DTN routing protocols can be categorized in to single and multi copy strategies A single copy strategy makes less use of network resources but suffers from long delay and less delivery probability Multi copy schemes enjoy better delivery probability and minimum delivery delay at the cost of heavy use of network resource Moreover DTN nodes operate under short contact duration and limited transmission bandwidth Therefore it is not possible for a node to transmit all messages from its forwarding queue Hence the order at which the messages are forwarded becomes very vital In this paper we propose a forwarding queue mode named MinHop We prove through simulations that the proposed policy performs better then FIFO in terms of delivery probability overhead message drop and rela

Opportunistic Networks: Present Scenario- A Mirror Review

Opportunistic Network is form of Delay Tolerant Network (DTN) and regarded as extension to Mobile Ad Hoc Network. OPPNETS are designed to operate especially in those environments which are surrounded by various issues like- High Error Rate, Intermittent Connectivity, High Delay and no defined route between source to destination node. OPPNETS works on the principle of “Store-and-Forward” mechanism as intermediate nodes perform the task of routing from node to node. The intermediate nodes store the messages in their memory until the suitable node is not located in communication range to transfer the message to the destination. OPPNETs suffer from various issues like High Delay, Energy Efficiency of Nodes, Security, High Error Rate and High Latency. The aim of this research paper is to overview various routing protocols available till date for OPPNETs and classify the protocols in terms of their performance. The paper also gives quick review of various Mobility Models and Simulation tools available for OPPNETs simulation

Maximizing Routing Throughput with Applications to Delay Tolerant Networks

abstract: Many applications require efficient data routing and dissemination in Delay Tolerant Networks (DTNs) in order to maximize the throughput of data in the network, such as providing healthcare to remote communities, and spreading related information in Mobile Social Networks (MSNs). In this thesis, the feasibility of using boats in the Amazon Delta Riverine region as data mule nodes is investigated and a robust data routing algorithm based on a fountain code approach is designed to ensure fast and timely data delivery considering unpredictable boat delays, break-downs, and high transmission failures. Then, the scenario of providing healthcare in Amazon Delta Region is extended to a general All-or-Nothing (Splittable) Multicommodity Flow (ANF) problem and a polynomial time constant approximation algorithm is designed for the maximum throughput routing problem based on a randomized rounding scheme with applications to DTNs. In an MSN, message content is closely related to users’ preferences, and can be used to significantly impact the performance of data dissemination. An interest- and content-based algorithm is developed where the contents of the messages, along with the network structural information are taken into consideration when making message relay decisions in order to maximize data throughput in an MSN. Extensive experiments show the effectiveness of the above proposed data dissemination algorithm by comparing it with state-of-the-art techniques.Dissertation/ThesisDoctoral Dissertation Computer Science 201

Adaptive Fuzzy Spray and Wait: Efficient Routing for Opportunistic Networks

The technological advancement in the area of wireless networking is ultimately envisioned to reach complete and seamless ubiquity, where every point on earth will need to be covered by Internet access. Low connectivity environments have emerged as a major challenge, and accordingly Opportunistic Networks arose as a promising solution. While these networks do not assume the existence of a path from the source to the destination, they opportunistically utilize any possible resource available to maximize throughput. Routing protocols in such environments have always tried to target an increased delivery probability, a shorter delay, and a reduced overhead. In this work, we try to balance these apparently conflicting goals by introducing “Adaptive Fuzzy Spray and Wait”, an optimized routing scheme for opportunistic networks. On top of the overhead reduction, we argue that the spray-based opportunistic routing techniques can attain higher delivery probability through integrating the adequate buffer prioritization and dropping policies. Towards that purpose, we employ a fuzzy decision making scheme. We also tackle the limitations of the previous approaches by allowing a full-adaptation to the varying network parameters. Extensive simulations using the ONE (Opportunistic Network Environment) simulator [1] show the robustness and effectiveness of the algorithm under challenged network conditions

A location aided controlled spraying routing algorithm for Delay Tolerant Networks

Delay Tolerant Networks (DTNs) often suffer from intermittent disruption and variable long delay due to factors such as mobility and energy. In this paper, a Location Aided Controlled Spraying (LACS) routing algorithm is proposed to deal with the challenging issues in DTN routing. Only the routing information carried by the contacted nodes is needed in this algorithm, and there is no need for global networks knowledge and hardware support. The routing process is divided into two stages, i.e., controlled spraying routing stage and single-copy routing stage. The maximum transfer throughput of the contact is checked before each message is forwarded. During the controlled spraying stage, the current node adjusts spraying strategy according to the encounter angle of the contact nodes. During the single-copy stage, a location prediction model based on the semi-Markov process (SMP) is introduced, and the node's behaviors can be captured both in the temporal and spatial domains with this model. The current node predicts the destination node's location, and then decides whether to forward the message to target node based on the time used for meeting the destination node. Simulation results show that the proposed algorithm can achieve better performance than the traditional routing schemes of DTNs in terms of delivery ratio, network overhead and transmission delay under both random node movement model and realistic trace scenario

Hybrid PRoPHET-Epidemic Routing Protocol for Optimizing Possibility of Sending Messages in Remote Fishermen Residential Area

Abstract—Limitations of communications facilities and infrastructure in the residential areas of the fishermen create problems of information difficulty. Lack of signal availability from the nearest Base Transceiver Station (BTS) that can reach the fishermen's residential area. A solution is needed that allows the communication path from the residential area of the fishermen to the area available for communication facilities and infrastructure. From this issue, there are several methods that can be used to overcome this problem. One of the methods that are used as a solution is Delay or Disruption Tolerant Network (DTN) network architecture, and another method utilize Crowdsource Mobile Access (CrowdMAC) to send message data packets to the destination device. In this paper, we carried out the integration of PRoPHET and Epidemic routing protocols to increase the level of the possibility of sending packets via multiple nodes with crowdsourcing. Index Terms—Crowdsource; Disruption Tolerant Network; Epidemic; PRoPHET

Enhanced Interest Aware PeopleRank for Opportunistic Mobile Social Networks

Network infrastructures are being continuously challenged by increased demand, resource-hungry applications, and at times of crisis when people need to work from homes such as the current Covid-19 epidemic situation, where most of the countries applied partial or complete lockdown and most of the people worked from home. Opportunistic Mobile Social Networks (OMSN) prove to be a great candidate to support existing network infrastructures. However, OMSNs have copious challenges comprising frequent disconnections and long delays. we aim to enhance the performance of OMSNs including delivery ratio and delay. We build upon an interest-aware social forwarding algorithm, namely Interest Aware PeopleRank (IPeR). We explored three pillars for our contribution, which encompass (1) inspect more than one hop (multiple hops) based on IPeR (MIPeR), (2) by embracing directional forwarding (Directional-IPeR), and (3) by utilizing a combination of Directional forwarding and multi-hop forwarding (DMIPeR). For Directional-IPeR, different values of the tolerance factor of IPeR, such as 25% and 75%, are explored to inspect variations of Directional-IPeR. Different interest distributions and users’ densities are simulated using the Social-Aware Opportunistic Forwarding Simulator (SAROS). The results show that (1) adding multiple hops to IPeR enhanced the delivery ratio, number of reached interested forwarders, and delay slightly. However, it increased the cost and decreased F-measure hugely. Consequently, there is no significant gain in these algorithms. (2) Directional-IPeR-75 performed generally better than IPeR in delivery ratio, and the number of reached interested forwarders. Besides, when some of the uninterested forwarders did not participate in messages delivery, which is a realistic behavior, the performance is enhanced and performed better generally in all metrics compared to IPeR. (3) Adding multiple hops to directional guided IPeR did not gain any enhancement. (4) Directional-IPeR-75 performs better in high densities in all metrics except delay. Even though, it enhances delay in sparse environments. Consequently, it can be utilized in disastrous areas, in which few people are with low connectivity and spread over a big area. In addition, it can be used in rural areas as well where there is no existing networks