2557933
Packet loss probability for DiffServ over IP and MPLS reliable homogeneous multicast networks
Multicasting has become increasingly important with the emergence of Internet-based applications such as IP telephony, audio/video conferencing, distributed databases and software upgrading. IP multicasting is an efficient way to distribute information from a single source to multiple destinations at different locations. In practice IP is considered as a layer 3 protocol. Multiprotocol Label Switching (MPLS) replaces the IP forwarding by a simple label lookup. MPLS combines the flexibility of layer 3 routing and layer 2 switching.In order to provide QoS in group communications for real time applications such as video conferencing, reliable multicasting is used. Miscellaneous efforts have been undertaken to provide reliability on top of IP multicast. Two error control strategies have been popular in practice. These are the FEC (Forward Error Correction) strategy, which uses error correction alone, and the ARQ (Automatic Repeat Request) strategy, which uses error detection, combined with retransmission of data.In this paper, we present a new fair share policy (FSP) that utilizes Differentiated Services to solve the problems of QoS and congestion control when reliable ARQ multicast is used. The results should provide insight into the comparisons of the residual packet loss probability between IP multicast in MPLS networks using FSP and plain IP multicasting using the same policy when DiffServ are adopted and when reliable ARQ multicast is considered.
23363151
Deploying multicast communication over MPLS networks using tree numbering
A new scheme for deploying multicasting in MPLS networks is proposed. Each possible tree in an MPLS network is assigned a number, which is then used to classify the corresponding multicast session into its FEC. We call this approach tree numbering (TN). It provides the capability to aggregate different multicast flows (sessions) having the same tree "shape". The assigned number is calculated distributedly by adding the partial weight values generated by the LSRs and the ingress LER of the corresponding tree. The key point in our approach is that the assigned numbers needed to distinguish the "shapes" of all the possible trees depend on the number of possible egress LERs could be reached by that ingress LERs and not on the number of the LSRs (core routers). In terms of the memory size, the proposed approach outperforms the approach that stores the IP addresses of the multicast tree or the one that store the concatenation of the sub codes generated by the ingress LER and the LSRs.
27266792
A unified approach to fault-tolerance in communication protocols based on recovery procedures
Discusses fault tolerance in computer communication protocols, modeled by communicating finite state machines, by providing an efficient algorithmic procedure for recovery in such systems. Even when the communication network is reliable and maintains the order of messages, any kind of transient error that may not be detected immediately could contaminate the system, resulting in protocol failure. To achieve fault-tolerance, the protocol must be able to detect the error, and then it must recover from that error and eventually reach a legal (or consistent) state, and resume its normal execution. A protocol that possesses the latter feature of recovering and continuing its execution starting from a legal state is also called a self-stabilizing protocol. Our recovery procedure does not require the application of an intrusive checkpointing procedure. The stable storage requirement for each process is less than that required for other proposed recovery procedures. The recovery procedure provides us with a legal protocol state, which is the global state before reaching any illegal state and before the effects of the error make other states illegal. Only a minimal number of processes affected by error propagation are required to rollback. Our recovery procedure can be used to recover from any number of transient errors in the system. Our recovery procedure has also been modeled in PROMELA, a language to describe validation models, which shows the syntactic correctness of our recovery protocol design. Finally, our procedure is compared with the existing approaches of handing the errors, and an illustrative example is provided.
13564962
Modelling and verification of interworking between SIP and H.323
There are currently two standards for signaling and control of Internet telephone calls, namely ITU-T Recommendation H.323 and the IETF session initiation protocol (SIP). Both protocols provide similar functionality using different mechanisms. Both H.323 and SIP provide interoperability, flexibility and scalability in different aspects and environments. Interworking between SIP and H.323 is essential to ensure full end-to-end connectivity through the network, although the current number of deployed commercial SIP endpoints is relatively small compared to widely deployed H.323 endpoints.To formally specify the SIP-H.323 Interworking, this paper gives a new system model for interworking between SIP and H.323. Five main components of this system are modeled using system description language and message sequence chart: H.323 endpoint, H.323 gatekeeper, SIP-H.323 Interworking facility, SIP server, SIP endpoint. We design and define the internal structure and behavior for each component, which is established for simulating and verifying interworking between SIP and H.323. Under two different configurations that both protocols work within the same administrative domain and that both protocols are operating in separate administrative domains, we use a series of scenarios to show that our model meets the functional specifications outlined in the SIP-H323-Interworking specification documents.
12571939
Inflight Rerouting for an Unmanned Aerial Vehicle
The availability of new information can often necessitate rerouting of a vehicle. In (1), the set of nonoverlapping useful vicinities of the reconnaissance sites, S, and the 3D space over them was represented using a discrete graph-model. Here, we consider two cases in which an unmanned reconnaissance aerial vehicle must be rerouted. The first scenario involves not visiting useful vicinities, S t ⊂ S, due to newly reported unacceptable threat- levels in their neighborhood. In the second scenario, visitations to useful vicinities, S r ⊂ S, is made redundant due to decreased importance of the sites to which they offer a vantage observation-point. Our earlier graph-model (1) is general enough to provide a basic framework for consideration of rerouting in both cases. We give an algorithm to obtain a graph-model, from the earlier one, that allows efficient gene encoding and efficient application of GA operators to obtain new alternative rerouting plans.
121937998
3D human pose from silhouettes by relevance vector regression
We describe a learning based method for recovering 3D human body pose from single images and monocular image sequences. Our approach requires neither an explicit body model nor prior labelling of body pans in the image. Instead, it recovers pose by direct nonlinear regression against shape descriptor vectors extracted automatically from image silhouettes. For robustness against local silhouette segmentation errors, silhouette shape is encoded by histogram-of-shape-contexts descriptors. For the main regression, we evaluate both regularized least squares and relevance vector machine (RVM) regressors over both linear and kernel bases. The RVM's provide much sparser regressors without compromising performance, and kernel bases give a small but worthwhile improvement in performance. For realism and good generalization with respect to viewpoints, we train the regressors on images resynthesized from real human motion capture data, and test it both quantitatively on similar independent test data, and qualitatively on a real image sequence. Mean angular errors of 6-7 degrees are obtained - a factor of 3 better than the current state of the art for the much simpler upper body problem.
7563707
Learning to track 3D human motion from silhouettes
We describe a sparse Bayesian regression method for recovering 3D human body motion directly from silhouettes extracted from monocular video sequences. No detailed body shape model is needed, and realism is ensured by training on real human motion capture data. The tracker estimates 3D body pose by using Relevance Vector Machine regression to combine a learned autoregressive dynamical model with robust shape descriptors extracted automatically from image silhouettes. We studied several different combination methods, the most effective being to learn a nonlinear observation-update correction based on joint regression with respect to the predicted state and the observations. We demonstrate the method on a 54-parameter full body pose model, both quantitatively using motion capture based test sequences, and qualitatively on a test video sequence.
6368187
Algorithms for derivation of structurally stable Hamiltonian signed graphs
A graph Sp,q,n refers to a signed graph with p nodes and q edges with n being the number of negative edges. We introduce two theorems to facilitate identification of the complete set of balanced signed graph configurations for any p-node Hamiltonian signed graph in terms of p, q and n. This allows for the development of computational procedures to efficiently determine the structural stability of a signed graph. This is potentially useful for the planning and analysis of complex situations or scenarios which can be depicted as signed graphs. Through the application of the theorems, the state of balance of a signed graph structure or its affinity towards balance can be determined in a more time-efficient manner compared to any explicit enumeration algorithm. E-mail: pg0212208t@ntu.edu.sg E-mail: fnh@crl.nmsu.edu E-mail: dwunsch@ece.umr.edu
660603
Algorithms for portfolio management based on the Newton method
We experimentally study on-line investment algorithms first proposed by Agarwal and Hazan and extended by Hazan et al. which achieve almost the same wealth as the best constant-rebalanced portfolio determined in hindsight. These algorithms are the first to combine optimal logarithmic regret bounds with efficient deterministic computability. They are based on the Newton method for offline optimization which, unlike previous approaches, exploits second order information. After analyzing the algorithm using the potential function introduced by Agarwal and Hazan, we present extensive experiments on actual financial data. These experiments confirm the theoretical advantage of our algorithms, which yield higher returns and run considerably faster than previous algorithms with optimal regret. Additionally, we perform financial analysis using mean-variance calculations and the Sharpe ratio.