Figure 8.9. Control of node movement. in Visual Studio .NET

Drawer QR Code 2d barcode in Visual Studio .NET Figure 8.9. Control of node movement.
Figure 8.9. Control of node movement.
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ALGORITHM 1. Sketch: The Optimal Relay Path to All Hosts in the System Input: 1. Initial time when host h0 begins to send a message. 2. The moving function of host hi , which gives the position of hi at time t. Output: The optimal moving path from host h0 to all other hosts h1 , h2 , , hn .
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Steps: 1. Compute the optimal trajectory for host h0 to reach all the other hosts directly, and record the earliest time point t[k] for hk . 2. Choose the unmarked host hi with the least t[i], mark hi , Ready[hi ] = 1. 3. Compute the optimal trajectory (use the Optimal Trajectory algorithm) for host h0 to reach all the unmarked hosts, such as hj by way of hi . If the time point computed for the optimal path from h0 to hj by way of hi is less than the original t[j], update t[j] with the newly computed time point. 4. Go to 2 until all the hosts have been marked.
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a message to the destination due to a network partition, it will try to do an up-call for the scheme presented. Algorithms that minimize the trajectory modi cations are developed under two different assumptions: (a) The movements of all the nodes in the system are known and (b) the movements of the hosts in the system are not known. In the rst case, the problem is, given a mobile ad hoc network (which may be disconnected) and the motion descriptions of the hosts (which is assumed to be known for all the movement of hosts), nding the shortest time strategy to send a message from one host to another. An optimal relay path algorithm is proposed and presented in Algorithm 1, which computes a sequence of intermediate hosts that can relay the message to the destination. Intermediate nodes modify their trajectories in the smallest possible way. In the second case, they propose a method in which hosts inform the other hosts of their current positions. The key issues that need to be considered to make this approach work are (1) when a host should send out information about its location update; (2) to whom the host should send out this information; and (3) how the host should send out this information. They model the communication problem in unknown mobile network environments by constructing a minimum spanning tree (MST), which contains the shortest edges in the graph that provide full connectivity in the graph. Each host has the responsibility of updating its location by informing all the hosts connected to it in the MST. However, their work assumes that the network is almost fully connected; it is not quite clear what happens if no such MST is found. In wireless networks, there usually are mismatches between available capacity and demand. When such a mismatch occurs in such networks, one way to add capacity is to increase the number of participants carrying bundles in the network. To achieve this, the work in reference 33 suggests the addition of a limited number of autonomous agents to the network area and studies the problem of augmenting the capacity of a DTN through autonomous agents which move in the network with the purpose of increasing network performance. The addition of these agents
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requires a control algorithm that can coordinate agent movements in order to optimize the performance of the network according to quality of service metrics desired by the network administrator. The authors present a control-based approach and develop multiobjective controllers to control the mobility of autonomous agents. The design of control strategies assumes the use of autonomous agents that can move to arbitrary locations in the physical environment. Four controllers latency, bundle latency, unique bandwidth and bandwidth are de ned in reference 33. Two approaches to multiobjective control subsumption and nullspace have been implemented and explored. Both techniques are from robotic research; nullspace controllers use linear algebra to coordinate controllers. Nullspace is de ned as the set of inputs to a function where the value of the function does not change. Nullspace composition is used to coordinate collections of controllers. The controllers are ordered in a way such that subordinate controller is forced to operate in the nullspace of controllers above it according to the order. The thresholded nullspace approach extends the nullspace approach to handle the networking situation that needed thresholded control. The subsumption approach differs from the nullspace approach in how the controllers dominate one another. Experimental results show that the thresholded nullspace approach outperforms the subsumption approach when resources are limited. Zhao et al. [34] describe a Message Ferrying (MF) approach for data delivery in sparse networks. MF is a proactive mobility-assisted approach that utilizes a set of special mobile nodes called message ferries to provide communication services for nodes in the network. Similar to their real-life analog, message ferries move around the deployment area and take responsibility for carrying data between nodes. The main idea behind the Message Ferrying approach is to introduce nonrandomness in the movement of nodes and exploit such nonrandomness to help deliver data. Two variations of the MF schemes were developed, depending on whether ferries or nodes initiate nonrandom proactive movement. In the Node-Initiated MF (NIMF) scheme, ferries move around the deployed area according to known speci c routes and communicate with other nodes they meet. With knowledge of ferry routes, nodes periodically move close to a ferry and communicate with that ferry. In NIMF, the ferry route is known by nodes for example, periodically broadcast by the ferry or conveyed by other out-of-band means. Nodes take proactive movement periodically to meet up with the ferry. As the sending node approaches the ferry, it forwards its messages to the ferry, which will be responsible for delivery. The trajectory control mechanism of the node determines when it should proactively move to meet the ferry for sending or receiving messages. The difference between NIMF and VMN is that the nodes movements are not controlled in VMN, whereas they are controlled in NIMF. In the Ferry-Initiated MF (FIMF) scheme, ferries move proactively to meet nodes. When a node wants to send packets to other nodes or receive packets, it generates a service request and transmits it to a chosen ferry using a long-range radio. Upon reception of a service request, the ferry will adjust its trajectory to meet up with the node and exchange packets using short-range radios. In both schemes, nodes can communicate with distant nodes that are out of range by using ferries as relays. It is
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