Congestion control and routing over challenged networks
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This dissertation is a study on the design and analysis of novel, optimal routing and rate control algorithms in wireless, mobile communication networks. Congestion control and routing algorithms upto now have been designed and optimized for wired or wireless mesh networks. In those networks, optimal algorithms (optimal in the sense that either the throughput is maximized or delay is minimized, or the network operation cost is minimized) can be engineered based on the classic time scale decomposition assumption that the dynamics of the network are either fast enough so that these algorithms essentially see the average or slow enough that any changes can be tracked to allow the algorithms to adapt over time. However, as technological advancements enable integration of ever more mobile nodes into communication networks, any rate control or routing algorithms based, for example, on averaging out the capacity of the wireless mobile link or tracking the instantaneous capacity will perform poorly. The common element in our solution to engineering efficient routing and rate control algorithms for mobile wireless networks is to make the wireless mobile links seem as if they are wired or wireless links to all but few nodes that directly see the mobile links (either the mobiles or nodes that can transmit to or receive from the mobiles) through an appropriate use of queuing structures at these selected nodes. This approach allows us to design end-to-end rate control or routing algorithms for wireless mobile networks so that neither averaging nor instantaneous tracking is necessary, as we have done in the following three networks. A network where we can easily demonstrate the poor performance of a rate control algorithm based on either averaging or tracking is a simple wireless downlink network where a mobile node moves but stays within the coverage cell of a single base station. In such a scenario, the time scale of the variations of the quality of the wireless channel between the mobile user and the base station can be such that the TCP-like congestion control algorithm at the source can not track the variation and is therefore unable to adjust the instantaneous coding rate at which the data stream can be encoded, i.e., the channel variation time scale is matched to the TCP round trip time scale. On the other hand, setting the coding rate for the average case will still result in low throughput due to the high sensitivity of the TCP rate control algorithm to packet loss and the fact that below average channel conditions occur frequently. In this dissertation, we will propose modifications to the TCP congestion control algorithm for this simple wireless mobile downlink network that will improve the throughput without the need for any tracking of the wireless channel. Intermittently connected network (ICN) is another network where the classic assumption of time scale decomposition is no longer relevant. An intermittently connected network is composed of multiple clusters of nodes that are geographically separated. Each cluster is connected wirelessly internally, but inter-cluster communication between two nodes in different clusters must rely on mobile carrier nodes to transport data between clusters. For instance, a mobile would make contact with a cluster and pick up data from that cluster, then move to a different cluster and drop off data into the second cluster. On contact, a large amount of data can be transferred between a cluster and a mobile, but the time duration between successive mobile-cluster contacts can be relatively long. In this network, an inter-cluster rate controller based on instantaneously tracking the mobile-cluster contacts can lead to under utilization of the network resources; if it is based on using long term average achievable rate of the mobile-cluster contacts, this can lead to large buffer requirements within the clusters. We will design and analyze throughput optimal routing and rate control algorithm for ICNs with minimum delay based on a back-pressure algorithm that is neither based on averaging out or tracking the contacts. The last type of network we study is networks with stationary nodes that are far apart from each other that rely on mobile nodes to communicate with each other. Each mobile transport node can be on one of several fixed routes, and these mobiles drop off or pick up data to and from the stationaries that are on that route. Each route has an associated cost that much be paid by the mobiles to be on (a longer route would have larger cost since it would require the mobile to expend more fuel) and stationaries pay different costs to have a packet picked up by the mobiles on different routes. The challenge in this type of network is to design a distributed route selection algorithm for the mobiles and for the stationaries to stabilize the network and minimize the total network operation cost. The sum cost minimization algorithm based on average source rates and mobility movement pattern would require global knowledge of the rates and movement pattern available at all stationaries and mobiles, rendering such algorithm centralized and weak in the presence of network disruptions. Algorithms based on instantaneous contact, on the contrary, would make them impractical as the mobile-stationary contacts are extremely short and infrequent.