15302993
DEFT: Distributed Exponentially-Weighted Flow Splitting
Network operators control the flow of traffic through their networks by adapting the configuration of the underlying routing protocols. For example, they tune the integer link weights that interior gateway protocols like OSPF and ISIS use to compute shortest paths. The resulting optimization problem -to find the best link weights for a given topology and traffic matrix -is computationally intractable even for the simplest objective functions, forcing the use of local-search techniques. The optimization problem is difficult in part because these protocols split traffic evenly along shortest paths, with no ability to adjust the splitting percentages or direct traffic on other paths. In this paper, we propose an extension to these protocols, called Distributed Exponentially-weighted Flow SpliTting (DEFT), where the routers can direct traffic on non-shortest paths, with an exponential penalty on longer paths. DEFT leads not only to an easier-to-solve optimization problem, but also to weight settings that provably perform no worse than OSPF and IS-IS. Furthermore, in our optimization problem, both link weights and flows of traffic are integrated as optimization variables into the formulation and jointly solved by a two-stage iterative method. Our novel formulation leads to a much more efficient way to identify good link weights than the local-search heuristics used for OSPF and IS-IS today. DEFT retains the simplicity of having routers compute paths based on configurable link weights, while approaching the performance of more complex routing protocols that can split traffic arbitrarily over any paths.
16311820
Optimal Provisioning of Elastic Service Availability
Service availability is one of the most closely scrutinized metrics in offering network services. The network vendor can earn more revenue from the customers by guaranteeing higher service availability at the cost of higher operational expense. It is important to cost-effectively provision a managed and differentiated network with various service availability guarantees under a unified platform. In this paper, we establish the framework of provisioning elastic service availability through network utility maximization, and propose an optimal and distributed solution using differentiated failure recovery schemes. First, we develop a utility function with configurable parameters to represent the satisfaction perceived by a user upon service availability as well as its allowed source rate. Second, adopting quality of protection [1] and shared path protection, we transform optimal provisioning of elastic service availability into a convex optimization problem. The desirable service availability and source rate for each user can be achieved using a price-based distributed algorithm. Finally, we numerically show the tradeoff between the throughput and the service availability obtained by users in various network topologies. Several quantitative observations are made from this investigation. For example, indiscriminately provisioning service availabilities for different kinds of users within one network leads to noteworthy sub-optimality in total network utility. The profile of bandwidth usage also illustrates that provisioning high service availability exclusively for critical applications leads to significant waste in bandwidth resource.
196020410
Distributed Partial Information Management (DPIM) schemes for survivable networks - Part I
15521655
An ultra-fast shared path protection scheme - distributed partial information management, part II
For pt.I see Chunming Qiao and Dahai Xu, INFOCOM'02, p.302-11, (2002). This paper describes a novel, ultra-fast heuristic algorithm to address an NP-hard optimization problem. One of its significances is that, for the first time, it is shown that a heuristic algorithm can also have better overall performance than its time-consuming, integer linear programming (ILP) based counterparts in the online case, which is non-intuitive. The proposed heuristic algorithm is useful for developing effective shared path (mesh) protection schemes that establish survivable connections in modern networks. The advantage of our heuristic algorithm over existing algorithms for finding a pair of link (or node) disjoint paths, active path (AP) and backup path (BP), comes from the following salient feature. It uses a so-called potential backup cost (PBC) function when selecting an AP in the first phase, in order to take into consideration the backup bandwidth needed by the corresponding BP yet to be chosen in the second phase. The PBC function is derived mathematically based on a rigorous statistical analysis of experimental data. While the use of PBC only requires partial aggregate information on existing connections and distributed control, it can also be applied even more effectively when complete information is available.
8591259
On the complexity of and algorithms for finding the shortest path with a disjoint counterpart
Finding a disjoint path pair is an important component in survivable networks. Since the traffic is carried on the active (working) path most of the time, it is useful to find a disjoint path pair such that the length of the shorter path (to be used as the active path) is minimized. In this paper, we first address such a Min-Min problem. We prove that this problem is NP-complete in either single link cost (e.g., dedicated backup bandwidth) or dual link cost (e.g., shared backup bandwidth) networks. In addition, it is NP-hard to obtain a K-approximation to the optimal solution for any K > 1. Our proof is extended to another open question regarding the computational complexity of a restricted version of the Min-Sum problem in an undirected network with ordered dual cost links (called the MSOD problem). To solve the Min-Min problem efficiently, we introduce a novel concept called conflicting link set which provides insights into the so-called trap problem, and develop a divide-and-conquer strategy. The result is an effective heuristic for the Min-Min problem called COnflicting Link Exclusion (COLE), which can outperform other approaches in terms of both the optimality and running time. We also apply COLE to the MSOD problem to efficiently provide shared path protection and conduct comprehensive performance evaluation as well as comparison of various schemes for shared path protection. We show that COLE not only processes connection requests much faster than existing integer linear programming (ILP)-based approaches but also achieves a good balance among the active path length, bandwidth efficiency, and recovery time.
14482795
Collaborative multi-agents for workflow management
Workflow management helps organizations to organize their work on different activities in such a way that the predictable underlying processes are carried out effectively and efficiently in a distributed environment. We describe a business workflow management system with intelligent multi-agent support in a collaborative organization environment. With the help from multi-agent collaboration, our workflow management system can organize the organization's work processes and provide resource control, data mediation, semantic mapping, and knowledge visualization processing. Such systems are able to manage the organizational workflow more effectively and more efficiently.
18166781
A State-Based Approach to Testing Aspect-Oriented Programs
This paper presents a state-based approach to testing aspect-oriented programs. Aspectual state models, as an extension to the testable FREE state model of classes, are exploited to capture the impact of aspects on the state models of classes. To generate test suites for adequately testing object behavior and interaction between classes and aspects in terms of message sequences, we transform an aspectual state model to a transition tree, where each path from the root to some leaf node indicates a template of test cases, i.e. message sequences. Since the statebased approach is directly built upon the test design patterns for object-oriented programs, it is not only applicable to the simultaneous development of classes and aspects, but also to the incremental development of aspects based on the existing classes.
8195983
Poisson shape interpolation
In this paper, we propose a novel shape interpolation approach based on Poisson equation. We formulate the trajectory problem of shape interpolation as solving Poisson equations defined on a domain mesh. A non-linear gradient field interpolation method is proposed to take both vertex coordinates and surface orientation into account. With proper boundary conditions, the in-between shapes are reconstructed implicitly from the interpolated gradient fields, while traditional methods usually manipulate vertex coordinates directly. Besides of global shape interpolation, our method is also applicable to local shape interpolation, and can be further enhanced by incorporating with deformation. Our approach can generate visual pleasing and physical plausible morphing sequences with stable area and volume changes. Experimental results demonstrate that our technique can avoid the shrinkage problem appeared in linear shape interpolation.
15674460
A two-stage logarithmic goal programming method for generating weights from interval comparison matrices
A two-stage logarithmic goal programming (TLGP) method is proposed to generate weights from interval comparison matrices, which can be either consistent or inconsistent. The first stage is devised to minimize the inconsistency of interval comparison matrices and the second stage is developed to generate priorities under the condition of minimal inconsistency. The weights are assumed to be multiplicative rather than additive. In the case of hierarchical structures, a nonlinear programming method is used to aggregate local interval weights into global interval weights. A simple yet practical preference ranking method is investigated to compare the interval weights of criteria or rank alternatives in a multiplicative aggregation process. The proposed TLGP is also applicable to fuzzy comparison matrices when they are transformed into interval comparison matrices using @a-level sets and the extension principle. Six numerical examples including a group decision analysis problem with a group of comparison matrices, a hierarchical decision problem and a fuzzy decision problem using fuzzy comparison matrix are examined to show the applications of the proposed methods. Comparisons with other existing procedures are made whenever possible.
14485762
Modeling and Analyzing Multi-Agent Behaviors Using Predicate/Transition Nets
How agents accomplish a goal task in a multi-agent system is usually specified by multi-agent plans built from basic actions (e.g. operators) of which the agents are capable. The plan specification provides the agents with a shared mental model for how they are supposed to collaborate with each other to achieve the common goal. Making sure that the plans are reliable and fit for the purpose for which they are designed is a critical problem with this approach. To address this problem, this paper presents a formal approach to modeling and analyzing multi-agent behaviors using Predicate/Transition (PrT) nets, a high- level formalism of Petri nets. We model a multi-agent problem by representing agent capabilities as transitions in PrT nets. To analyze a multi-agent PrT model, we adapt the planning graphs as a compact structure for reachability analysis, which is coherent to the concurrent semantics. We also demonstrate that one can analyze whether parallel actions specified in multi-agent plans can be executed in parallel and whether the plans can achieve the goal by analyzing the dependency relations among the transitions in the PrT model.