Backpressure Based Adaptive Routing and Scheduling In Delay Tolerant Network

In order to avoid this problem, a technique called probability distribution algorithm is introduced. In probability distribution algorithm, the random traffic between the primary network users are analyzed. The nearby nodes behaviors are learnt by the secondary node. The probability of the traffic in the neighboring nodes are studied by the node that tries to transmit data. When the traffic is free then the secondary node establishes the connection. If there is traffic then the secondary node searches for other nodes. Thus the data transmission occurs in this CR

Simulation environment consists of wired, wireless and wired cum wireless network. Network simulator NS 2.35 [6] is used for the simulation. NS is a discrete event simulator, where the advance of times depends on the timing of events which are maintained by simulator.

To ensure QoS in our proposed algorithm we calculate the utility of a node e.g. $node_i$ as the summation of remaining CPU cycle ($R_{CPU_i}$), remaining memory in that node ($R_{mem_i}$), remaining bandwidth available for that node ($R_{bw_i}$), remaining data reside in the buffer to transmit ($R_{data_i}$), data rate ($Data_{rate_i}$) and priority of data to be transmitted $Pri_{data_i}$.

Identification of user location whether the user is nearer to the BS or moving away from the BS. When the user is nearer to the BS, there will be continuous service, all the remaining BS which is not active could be put into sleep. SDN concept to the energy saving and optimizing problems in wireless access network to solve the “channel state prediction problem”, which in fact is the correlation between user’s location and channel capacity. If a user’s future location is predictable, the upcoming data rates can be anticipated from “wireless coverage information” stored in the network controller database. This protocol is between control plane and data plane, and it can support the feasibility of SDN. The database is able to be updated in real-time by the corresponding strategy Stored in users terminals. The energy consumption of BSs is more than 50% of all energy used in the wireless access network Consequently, the research of energy saving in BSs is essential

There have been a lot of situations where we have seen loss of packets while transferring data. Therefore, multi-hop wireless ad hoc network has identified

We then optimize the link weights taking only the critical link failures into account. We want to avoid that the failure of heavily loaded links results in large amounts of traffic being recovered in backup configurations with a sparse backbone. Instead, this traffic should be routed in a rich (well connected) backbone, where we have abetter chance of distributing it over less loaded links by settingappropriate link weights.To implement this load-aware algorithm we calculate the potentialof each node in the network and the potential of each backup configuration.

We set up a testbed to assess the proposed calculations. Two entrance systems, WiFi and Ethernet are joined with the VAN server, and the VAN server additionally functions as the door to people in general Internet. The WiFi connection is constrained to 2 Mbps, the Ethernet join for imitating the Cellular connection is restricted to 4 Mbps to consider asset limits, for example, foundation traffic, for instance. The high edge β is situated to 50 s and the discriminating limit off is situated to 20 s.

There are number of metrics which are helpful for deciding the efficiency of a protocol. In this work the parameters used to evaluate the efficiency of a protocol are the packet delivery ratio, packet statistics in the network and the throughput of the network. The protocols AODV and AODVBC are checked against these parameters for their performance. Packet delivery ratio of the network is improved as the mobility with respect to the number of nodes changes. Increase in the PDR (Packet delivery ratio is because of the less number of packet drops when AODVBC is used. Fig. 4 justifies the better performance of AODVBC routing protocol over AODV protocol in terms of less number of packets drop.

With the drop of the hardware cost, more and more mobile devices with higher capacities are now used. The widely deployed wireless LAN and broadband wireless networks provide the ubiquitous network access for multimedia applications. Provision of Quality of Service (QoS) is challenging in mobile ad hoc networks because of the dynamic characteristics of mobile networks and the limited resources of the mobile devices. The wireless network is not reliable due to node mobility, multi-access channel and multi-hop communication.

Abstract- Delay Tolerant Networks are intermittent networks which don’t have constant connectivity between its nodes. Though it has evolved from mobile ad-hoc network (MANET), its protocols cannot be used because of intermittency. They have finite coverage of bandwidth, nodes that are scattered widely (which can be mobile), limited energy resources, variable delay and data rates that vary according to direction. This leads to high error rate. Such networks can be in extreme terrestrial locations or planned networks in space. Since DTNs are prone to

The Backward explicit congestion notification (BECN) \cite{newman1993backward}\cite{newman1994traffic} is different from FECN. Instead of returning RM cell by the destination-end, the congestion information is directly sent back to the source by the congested point (switch). As shown in Fig. \ref{BECN}, when the queue of a virtual channel exceeds a fixed threshold, the switch will directly send BECN cells to the source that contribute to the congestion. On each receiving of a BECN cell, the source reduces the sending rate of the specific virtual channel. If no BECN cell arrives on the throttled virtual channel for a time period, the sending rate will be gradually regained.\

Thus, a mobile station able to operate on several technologies should roam freely from one interface to another, being able to maintain its network connection and the QoS required by higher layer applications. The vertical handover is a very important capability in the future wireless communication era, where an integrated network grouping multiple technologies will try to offer a global broadband access to mobile users. However, compared to the horizontal handover, the signal strength metric is sometimes not suited and often not sufficient to appropriately trigger the vertical handover: as heterogeneous networks have different system characteristics, their performance cannot be simply compared using the signal strength of two cells [12]. At a particular position, there may be more than one network (WLAN, WCDMA and Wi-Max) available. On the other hand it may happen that the desired network, through which the vehicle is communicating currently, is not available at a particular area. Thus it is required to change the network immediately to ensure QoS. Vertical handoff enables seamless terminal, personal and network mobility. It provides for continuity and transfer of existing sessions. Vertical handoff can be separated into three phases: network discovery, handoff decision, and handoff execution [8]. This paper aims at defining an efficient user-driven vertical handover mechanism which does not require any change on network and Protocol

1 shows a multi-home circumstance where a Mobile device is related with both Base Station and Access point through its various interfaces. MPTCP works commendably for multi-homed phones to in the meantime pass on TCP packages over various ways and pool the open information exchange limit together. Despite the way that MPTCP has a prevalent available throughput for the upper layer, there is as yet another questionable issue realized by out-of-solicitations bundles. Throughput addresses the general getting point of confinement of powerful bundle movement over various ways. Regardless, it is extraordinary put that mirrors the certified application-level throughput, which is the measure of accommodating data available to the recipient application per time unit. Specifically, all together packages got at the vehicle layer can be sent to the application layer and implied extraordinary put. Most recent review [7] gave CWA a proactive scheduler for wired correspondence. This review show that MPTCP extraordinary put is close perfect when the end-to end deferments of two transmission ways are close. However these review exhibit that it requires a significant measure of venture to reorder packs at getting end. Some later work in 2012 tries to improve incredible put for MPTCP, by using framework coding [2]

Mobile ad-hoc networks (MANET) are characterized as networks without any physical connections. In these networks there is no fixed topology due to the mobility of nodes, interference, multipath propagation and path loss. Hence a dynamic routing protocol is needed for these networks to function properly. Many Routing protocols have been developed for accomplishing this task. MANET routing protocols can be categorized as Proactive or Table-driven Routing Protocols Reactive or On Demand routing protocols and Hybrid routing protocols. This paper presents the three types of routing protocols in MANET and makes a comparative discussion of the features of each type of that routing protocol.

Delay Tolerant Network (DTN) represents a class of wireless networks that has no connected path between a source and the destination. The network is partitioned into several sub-networks in DTN. DTNs represent a class of wireless systems with no infrastructure and support the functionality of networks experiencing recurrent and long lasting partitions. Delay tolerant networking [1] has received major attention in recent years. Since in DTN, the destination path is not connected, so the main purpose here is to find the intermediate nodes for routing the packets [2, 3]. When two nodes come in contact with each other, they may exchange the packets and such an occasion is known as encounter. In DTN, store-carry-forward model is used for packet delivery. According to this model, each node along the