Efficient and distributed computation of maximum multicast rates
The transmission of information within a data network is constrained by network topology and link capacities. In this paper, we study the fundamental upper bound of information multicast rates with these constraints, given the unique replicable and encodable property of information flows. Based on recent information theory advances in coded multicast rates, we are able to formulate the maximum multicast rate problem as a linear network optimization problem, assuming the general undirected network model. We then proceed to apply Lagrangian relaxation techniques to obtain (1) a necessary and sufficient condition for multicast rate feasibility, and (2) a subgradient solution for computing the maximum rate and the optimal routing strategy to achieve it. The condition we give is a generalization of the well-known conditions for the unicast and broadcast cases. Our subgradient solution takes advantage of the underlying network flow structure of the problem, and therefore outperforms general linear programming solving techniques. It also admits a natural intuitive interpretation, and is amenable to fully distributed implementations.

title: Probabilistic Power Management for Wireless Ad Hoc Networks
abstract: Extending system lifetime by effectively managing power on participating nodes is critical in wireless ad hoc networks. Recent work has shown that, by appropriately powering off nodes, energy may be significantly saved up to a factor of two, especially when node density is high. Such approaches rely on the selection of a virtual backbone (i.e., a connected dominating set) of the topology to forward ongoing traffic, coupled with algorithms to manually and periodically recompute such a backbone for load balancing purposes. The common drawback of such schemes is the need to involve periodic message exchanges and to make additional restrictive assumptions. This paper presents Odds1, an integrated set of energy-efficient and fully distributed algorithms for power management in wireless ad hoc networks. Odds build on the observation that explicit and periodic re-computation of the backbone topology is costly with respect to its additional bandwidth overhead, especially when nodes are densely populated or highly mobile. Building on a fully probabilistic approach, Odds seek to make a minimum overhead, perfectly balanced, and fully localized decision on each node with respect to when and how long it needs to enter standby mode to conserve energy. Such a decision does not rely on periodic message broadcasts in the local neighborhood, so that Odds are scalable as node density increases. Detailed mathematical analysis, discussions and simulation results have shown that Odds are indeed able to achieve our objectives while operating in a wide range of density and traffic loads.

title: On increasing end-to-end throughput in wireless ad hoc networks
abstract: One of the main characteristics of wireless ad hoc networks is their node-centric broadcast nature of communication, leading to interferences and spatial contention between adjacent wireless links. Due to such interferences, pessimistic concerns have been recently raised with respect to the decreasing network capacity in wireless ad hoc networks when the number of nodes scales to several orders of magnitude higher. In this paper, we argue that in all cases of end-to-end data communications - including one-to-k unicast and multicast data dissemination as well as k-to-one data aggregation - the maximum achievable end-to-end data throughput (measured on the sources) heavily depends on the strategy of arranging the topology of transmission between sources and destinations, as well as possible per-node operations such as coding. An optimal strategy achieves better end-to-end throughput than an arbitrary one. We present theoretical studies and critical insights with respect to how these strategies may be designed so that end-to-end throughput may be increased

title: sFlow: towards resource-efficient and agile service federation in service overlay networks
abstract: Existing research work towards the composition of complex federated services has assumed that service requests and deliveries flow through a particular service path or tree. Here, we extend such a service model to a directed acyclic graph, allowing services to be delivered via parallel paths and interleaved with each other. Such an assumption of the service flow model has apparently introduced complexities towards the development of a distributed algorithm to federate existing services, as well as the provisioning of the required quality in the most resource-efficient fashion. To this end, we propose sFlow, a fully distributed algorithm to be executed on all service nodes, such that the federated service flow graph is resource efficient, performs well, and meets the demands of service consumers.

title: iFlow: Middleware-assisted Rendezvous-based Information Access for Mobile Ad Hoc Applications
abstract: Due to node mobility and limitations on bandwidth availability in wireless channels, there exist unique challenges towards achieving efficient and effective information access in wireless ad hoc networks with mobile nodes. In this paper, we address two critical questions: (1) How may information be accessed with the highest degree of bandwidth efficiency? and (2) How should algorithms be designed so that node mobility contributes positively towards high performance and efficiency? We present iFlow, a middleware-based framework for bandwidth-efficient and delay-aware information access for mobile ad hoc applications. We present the case of information rendezvous, where the demands for information are satisfied by the supplies in a fully distributed fashion, across third-party nodes beyond information suppliers and consumers. Such rendezvous is achieved via controlled diffusion of information from the suppliers, matched by the gleaning process on the consumers. We validate our claims using simulation and experimental results.

title: On achieving maximum multicast throughput in undirected networks
abstract: The transmission of information within a data network is constrained by the network topology and link capacities. In this paper, we study the fundamental upper bound of information dissemination rates with these constraints in undirected networks, given the unique replicable and encodable properties of information flows. Based on recent advances in network coding and classical modeling techniques in flow networks, we provide a natural linear programming formulation of the maximum multicast rate problem. By applying Lagrangian relaxation on the primal and the dual linear programs (LPs), respectively, we derive a) a necessary and sufficient condition characterizing multicast rate feasibility, and b) an efficient and distributed subgradient algorithm for computing the maximum multicast rate. We also extend our discussions to multiple communication sessions, as well as to overlay and ad hoc network models. Both our theoretical and simulation results conclude that, network coding may not be instrumental to achieve better maximum multicast rates in most cases; rather, it facilitates the design of significantly more efficient algorithms to achieve such optimality.

title: IDGraphs: intrusion detection and analysis using stream compositing
abstract: IDGraphs is an interactive visualization system, supporting intrusion detection over massive network traffic streams. It features a novel time-versus-failed-connections mapping that aids in discovery of attack patterns. The number of failed connections (SYN-SYN/ACK) is a strong indicator of suspicious network flows. IDGraphs offers several flow aggregation methods that help reveal different attack patterns. The system also offers high visual scalability through the use of Histographs. The IDGraphs intrusion detection system detects and analyzes a variety of attacks and anomalies, including port scanning, worm outbreaks, stealthy TCP SYN flooding, and some distributed attacks. In this article, we demonstrate IDGraphs using a single day of NetFlow network traffic traces collected at edge routers at Northwestern University which has several OC-3 links.

title: Rate-distortion optimal video summary generation
abstract: The need for video summarization originates primarily from a viewing time constraint. A shorter version of the original video sequence is desirable in a number of applications. Clearly, a shorter version is also necessary in applications where storage, communication bandwidth, and/or power are limited. The summarization process inevitably introduces distortion. The amount of summarization distortion is related to its "conciseness", or the number of frames available in the summary. If there are m frames in the original sequence and n frames in the summary, we define the summarization rate as m/n, to characterize this "conciseness". We also develop a new summarization distortion metric and formulate the summarization problem as a rate-distortion optimization problem. Optimal algorithms based on dynamic programming are presented and compared experimentally with heuristic algorithms. Practical constraints, like the maximum number of frames that can be skipped, are also considered in the formulation and solution of the problem.

title: Buffer insertion in large circuits with constructive solution search techniques
abstract: Most existing buffer insertion algorithms, such as van Ginneken's algorithm, consider only individual nets. As a result, these algorithms tend to over buffer when applied to combinational circuits, since it is difficult to decide how many buffers to insert in each net. Recently, Sze, et al.  proposed a path-based algorithm for buffer insertion in combinational circuits. However their algorithm is inefficient for large circuits when there are many critical paths. In this paper, we present a new buffer insertion algorithm for combinational circuits such that the timing requirements are met and the buffer cost is minimized. Our algorithm iteratively inserts buffers in the circuit to improve the circuit delay. The core of this algorithm is simple but effective technique that guides the search for a good buffering solution. Experimental results on ISCAS85 circuits show that our new algorithm on average uses 36% less buffers and runs 3 times faster than Sze's algorithm

title: Parametric analysis for adaptive computation offloading
abstract: Many programs can be invoked under different execution options, input parameters and data files. Such different execution contexts may lead to strikingly different execution instances. The optimal code generation may be sensitive to the execution instances. In this paper, we show how to use parametric program analysis to deal with this issue for the optimization problem of computation offloading.Computation offloading has been shown to be an effective way to improve performance and energy saving on mobile devices. Optimal program partitioning for computation offloading depends on the tradeoff between the computation workload and the communication cost. The computation workload and communication requirement may change with different execution instances. Optimal decisions on program partitioning must be made at run time when sufficient information about workload and communication requirement becomes available.Our cost analysis obtains program computation workload and communication cost expressed as functions of run-time parameters, and our parametric partitioning algorithm finds the optimal program partitioning corresponding to different ranges of run-time parameters. At run time, the transformed program self-schedules its tasks on either the mobile device or the server, based on the optimal program partitioning that corresponds to the current values of run-time parameters. Experimental results on an HP IPAQ handheld device show that different run-time parameters can lead to quite different program partitioning decisions.

title: QMBF: a QoS-aware multicast routing protocol
abstract: Many multicast applications, such as video-on-demand and tele-education, desire quality of service (QoS) support from the underlying network. Recently, many QoS-based multicast protocols have been proposed to meet this requirement. However, few of them can achieve high success ratios while maintaining good scalability. In this paper, we propose a new QoS-aware multicast protocol based on a bounded flooding technique (QMBF). In this protocol, every network node maintains the knowledge of a local network cell (LNC) topology as well as QoS state information (collected from the bounded flooding messages). QMBF utilizes this knowledge to increase the probability and accuracy of finding a feasible branch which connects a new member to an existing multicast tree. The protocol exploits two approaches to find feasible branches: repeatedly computing partial feasible branches using the LNC information and searching multiple paths. The design of QMBF allows it to operate on top of any unicast routing protocol or cooperate with a QoS-based unicast routing protocol. Results obtained using NS-2 simulator demonstrate high success ratio for locating feasible branches for multicast paths.