Parameterized complexity of spare capacity allocation and the multicost Steiner subgraph problem

Optical mesh network infrastructure has emerged as the technology of choice for next-generation transport networks. At the same time, distributed, IP-based, control architecture has been proposed for intelligent optical networks, as a means to automate operations, enhance interoperability, and facilitate the deployment of new applications. While distributed control in general enhances scalability and flexibility, it has also been observed that the requisite network topology and link-state information summarization may result in suboptimal path computation, especially for shared mesh restored paths. This paper presents a distributed control plane for optical mesh networks, focusing on distributed path computation and provisioning mechanisms. It discusses the tradeoffs between the path computation efficiency for shared mesh restored paths and the amount of network topology and link-state information that is disseminated via routing protocols. We show that with appropriately aggregated link resource availability and sharing information, the proposed distributed path computation algorithms are able to determine the shareability of restoration links with remarkable accuracy. A local channel assignment scheme, which is used in conjunction with the distributed path computation algorithms to assign shared channels when provisioning restoration paths, is also proposed. The additional information that signaling messages are required to carry in order to perform the local channel assignment at each node along the restoration path is discussed. Furthermore, we specify the extensions to the open shortest-path first (OSPF) routing protocol in support of shared mesh restoration. We analyze the performance of the proposed distributed path computation algorithms and the local channel assignment scheme, as well as the overhead of OSPF extensions. In particular, we study the tradeoffs between network capacity utilization, restoration path computation complexity, OSPF extension overhead, and memory requirements for storing the modified link-state database.

Clinical decision making requires knowledge, experience and analytical/non-analytical types of decision processes. As clinicians progress from novice to expert, research indicates decision-making becomes less reliant on foundational biomedical knowledge and more on previous experience. In this study, we investigated how knowledge and experience were reflected in terms of differences in neural areas of activation. Novice and expert clinicians diagnosed simple or complex (easy, hard) cases while functional magnetic resonance imaging (fMRI) data were collected. Our results highlight key differences in the neural areas activated in novices and experts during the clinical decision-making process. fMRI data were collected from ten second year medical students (novices) and ten practicing gastroenterologists (experts) while they diagnosed sixteen (eight easy and eight hard) clinical cases via multiple-choice questions. Behavioral data were collected for diagnostic accuracy (correct/incorrect diagnosis) and time taken to assign a clinical diagnosis. Two analyses were performed with the fMRI data. First, data from easy and hard cases were compared within respective groups (easy>hard, hard>easy). Second, neural differences between novices and experts (novice>expert, expert>novice) were assessed. Experts correctly diagnosed more cases than novices and made their diagnoses faster than novices on both easy and hard cases (all p's<0.05). Time taken to diagnose hard cases took significantly longer for both novices and experts. While similar neural areas were activated in both novices and experts during the decision making process, we identified significant hemispheric activation differences between novice and expert clinicians when diagnosing hard clinical cases. Specifically, novice clinicians had greater activations in the left anterior temporal cortex and left ventral lateral prefrontal cortex whereas expert clinicians had greater activations in the right dorsal lateral, right ventral lateral, and right parietal cortex. Hemispheric differences in activation were not observed between novices and experts while diagnosing easy clinical cases. While clinical decision-making engaged the prefrontal cortex (PFC) in both novices and experts, interestingly we observed expertise related differences in the regions and hemispheres of PFC activation between these groups for hard clinical cases. Specifically, in novices we observed activations in left hemisphere neural regions associated with factual rule-based knowledge, whereas in experts we observed right hemisphere activation in neural regions associated with experiential knowledge. Importantly, at the neural level, our data highlight differences in so called type 2 clinical decision-making processes related to prior knowledge and experience.

The Judiciary and Fiscal Crises: An Institutional Critique

This paper proposes a new optical path restoration method for wavelength division multiplexing (WDM) networks. In the method, the protection path is established by connecting several sub-lightpaths from the source node to the destination node of the original working lightpath, as opposed to conventional path restoration where a single protection lightpath between the source-destination pair performs restoration. The set of one or more consecutive lightpaths to connect a source-destination pair is called semi-lightpath. The semi-lightpath based restoration provides enhanced flexibility in protection path provisioning and relieves the cost of spare capacity reservation and wavelength conversion at intermediate optical cross-connect nodes. In terms of spare capacity utilization, our method shows substantial reduction of spare capacity overhead compared with dedicated path restoration in all optical networks without wavelength conversion, and shows similar capacity efficiency compared with shared path restoration in opaque networks with full wavelength conversion capability.

In recent years, p-cycles have been widely investigated for survivability of WDM networks. They provide fast recovery speed such as ring and capacity efficiency as mesh survivability schemes. However, restoration paths are very long, which causes excessive latency and intolerable physical impairments. On the other hand, nowadays, a wide set of applications require an optical path with almost no delay. The existing approaches, namely loopbacks removal and inter-cycle switching, provide a significant reduction in the restored path, but even then a number of restored paths remain many times longer than the working path lengths. In this paper, we propose a network partitioning-based approach to control the length of each restored path as per delay sustainability of time critical applications. The basic idea of the work is to partition the network into domains and construct the p-cycles for each domain independently. The domain wise construction of p-cycles restricts their length, which consequently reduces the length of restored paths. Here, we introduce a new concept where the selected border nodes are overlapped among adjacent domains to cover inter-domain spans of the network as a domain span in order to ensure their survivability through domain p-cycles. Simulation results show that the proposed solution is good enough to control the restored path length with small augmentation in redundancy of spare capacity as compared to optimal design of p-cycles. More importantly, it enhances the dual failure restorability significantly.

Legal Realism Untamed

In this paper, a computationally efficient algorithm for level set based tracking is suggested for near real-time implementation. The problem of computational complexity in level set based tracking is tackled by combining a sparse field level set method (SFLSM) with a Rao-Blackwellized particle filter (RBPF). Under the RBPF framework, affine motion is estimated using an appearance-based particle filtering (PF) to provide the initial curves for SFLSM and the local deformation of contours is analytically estimated through SFLSM. SFLSM is adopted to significantly reduce the computational complexity of the level set method (LSM) implementation. For the initial curve estimation in SFLSM, the estimated position and object scale are provided by the appearance-based PF in order to achieve the desired efficiency. Furthermore, the appearance-based PF alleviates inaccurate segmentation incurred by an incorrect initial curve. Experimental results with a real-video confirm the promising performance of this method.

Wavelength Division Multiplexed (WDM) networks that route optical connections using intelligent optical cross-connects (OXCs) is firmly established as the core constituent of next generation networks. Rapid failure recovery is fundamental to building reliable transport networks. Mesh restoration promises cost effective failure recovery compared with legacy ring networks, and is now seeing large-scale deployment. Many carriers are migrating away from SONET ring restoration for their core transport networks and replacing it with mesh restoration through “intelligent” O-E-O cross-connects (XC). The mesh restoration is typically provided via two fiber-disjoint paths: a service path and a restoration path. this scheme can restore any single link failure or node failure. And by used shared mesh restoration, although every service route is assigned a restoration route, no dedicated capacity needs to be reserved for the restoration route, resulting in capacity savings. The restoration approach we propose is Centralized Pre-computing, Local Distributed Optimization, and Shared Disjoint-backup Path. This approach combines the merits of centralized and distributed solutions. It avoids the scalability issues of centralized solutions by using a distributed control plane for disjoint service path computation and restoration path provisioning. Moreover, if the service routes of two demands are disjoint, no single failure will affect both demands simultaneously. This means that the restoration routes of these two demands can share link capacities, because these two routes will not be activated at the same time. So we can say, this restoration capacity sharing approach achieves low restoration capacity and fast restoration speed, while requiring few control plane changes.

Today, the most promising technique used for the survivability of optical transport networks is p-cycle. However, it provides longer restoration path at failure state of the network. The intercycle switching (ICS) is one of the recent approaches that is based on idle p-cycles and is used for shortening the length of restoration path in single-fault model. Utilization of idle p-cycles degrades the inherent dual-failure restorability of single-failure design model of p-cycle, whereas ICS releases the maximum portion of conventional restoration path by utilizing a small segment of the idle p-cycle. Here, the authors proposed a new approach to reconfiguring the released portion of restoration path and unused segment of corresponding idle p-cycle as new cycle(s). In respect of idle p-cycles, the new reconfigured cycle(s) provides more dual-failure restorability in single-failure design of p-cycle. Therefore, the proposed approach mitigates the above-said drawback of ICS and minimizes additional spare capacity requirement for dual-failure survivability.

In quantum key distribution (QKD) networks, the quantum service channel (QSCh) is highly sensitive to link failures, as any interruption in the quantum channel can immediately halt key generation, and hence the transmission of secured data across optical networks. Hence, robust protection mechanisms are essential to ensure continuous secure key distribution. However, conventional protection approaches, such as dedicated protection and fixed-path routing, often suffer from low resource efficiency and poor adaptability to heterogeneous relay environments. To ensure both survivability and efficient resource allocation in QKD based optical networks, we propose a shared path protection scheme based on hybrid relays. In the proposed approach, K-candidate paths are computed for both the traditional data channel (TDCh) and QSCh, and the working path is selected using a weighted metric that considers both the hop-count and the security degree. To enhance resilience, the shared protection paths are established, allowing multiple backup paths to reuse network resources for connection requests. A connection request is accepted only if both the working and the protection paths are successfully reserved, thereby ensuring strong protection. The system incorporates joint allocation of wavelength and time-slot, and introduces a protection threshold to support shared use of backup resources. Simulation results show that the proposed method achieves lower blocking probability, while maintaining high wavelength and time-slot efficiency compared to the baseline methods in different networks.

Low Earth Orbit (LEO) satellites utilizing Doppler measurements can be an effective supplementary positioning solution when Global Navigation Satellite System (GNSS) signals are unavailable. LEO satellites pose challenges to the efficiency and stability of real-time satellite selection algorithms due to their high dynamic and large number. The traditional satellite selection algorithms have the problems of high computational complexity and significant hardware dependence. In contrast, the intelligent optimization algorithm significantly improves the accuracy and real-time performance of satellite selection through global search and efficient processing. According to the characteristics of LEO satellites, a Multi-Strategy Fusion Grey Wolf Optimization (MSFGWO) algorithm is proposed for satellite selection. The experimental results show that when six satellites are selected, the average Doppler Geometric Dilution of Precision (DGDOP) value of the MSFGWO algorithm is 222.08. Compared with the DGDOP ratio of the traversal method, it is 1.03. The three-dimensional positioning accuracy is 192.86 m, and the positioning error is improved by 54.43% compared with the positioning accuracy of the traditional GWO algorithm. The longest continuous observation was achieved for 45 s, during which no switching of six satellites occurred at adjacent moments. The calculation time of the algorithm was only 0.0174 s, and the efficiency was improved by 93.43%. The MSFGWO algorithm proposed in this paper not only improves the overall optimization ability of the Grey Wolf Optimizer (GWO) algorithm and effectively reduces the DGDOP value but also significantly reduces the satellite switching number and prolongates the continuous observation time, thus improving the stability and accuracy of the positioning solution.

How Many Cases are Easy?

The concept of the shortest (or minimum) spanning tree (SST)and recursive SST (RSST) of an undirected weighted graph has been successfully applied in image segmentation and edge detection. This paper presents a divide-and-conquer approach for (R)SST based image segmentation in order to overcome the problem of high computational complexity associated with conventional graph algorithms. In the simplest form, the proposed approach, block-based RSST (BRSST), first divides the image into rectangular blocks, finds the (R)SST of each block individually using conventional graph algorithms and, then, merges the (R)SSTs of all image blocks to form an (R)SST of the entire image. Efficient merging algorithms are presented in this paper. We proved a theorem showing that the (R)SST obtained by the merging algorithms is one of the (R)SST that would be found by applying to the entire image the same algorithm used for finding the (R)SST of each image block. Theoretical analysis and experimental results have shown that BRSST has significantly reduced the computational cost. In addition, an incremental BRSST is proposed for video segmentation and results are presented

Optical Burst-Switched (OBS) networks usually employ one-way reservation by sending a burst control packet (BCP) with a specific offset time, before transmitting each data burst frame (BDF). Therefore, a fiber link failure may lead to loss of several BDFs as the ingress nodes sending these BDFs remain unaware of the failed link till they receive the failure indication signal (FIS). In this paper, we propose a hybrid restoration scheme, wherein we employ a novel combination of sub-path as well as path restoration schemes. In particular, the upstream node preceding the failed link employs sub-path restoration as soon as it detects the failure. Thereafter, when the source ingress node receives the FIS message, it (source ingress node) takes over the responsibility and employs path restoration. However, sub-path restoration is exercised by the upstream node only if the remaining time intervals left for the yet-to-arrive BDFs (for which BCPs have already left the upstream node) are less than a minimum time interval (called as threshold reaction time). Performance of the proposed scheme is evaluated through extensive computer simulation using OPNET. Our results indicate that the proposed restoration scheme significantly reduces burst losses due to link failure and, thus, outperforms the existing restoration schemes.

Due to the high data rates in optical networks,physical-layer attacks targeting service degradation, such as powerjamming, can potentially lead to large data and revenue losses.Conventional network survivability approaches which establishlink-disjoint working and backup paths to protect from componentfaults may not provide adequate protection for such attacks.Namely, the working and the backup paths, although link-disjoint,might both be affected by a single attack scenario due to specificattack propagation characteristics. To enhance the existing survivabilityapproaches, we utilize the concept of an attack group(AG) which incorporates these characteristics to identify connectionswhich can simultaneously be affected by a single attack. Weapply this concept to dedicated path protection (DPP) and developattack-aware DPP (AA-DPP) approaches which aim to establishAG-disjoint primary and backup paths in a cost-effective manner.We provide a two-step ILP formulation for the routing and wavelengthassignment of the working and backup paths, as well as aheuristic for larger problem instances. Numerical results indicatethat the proposed approaches provide dedicated path protectionschemes with enhanced attack protection without using more resources(i.e., wavelengths, average path lengths) than standardDPPmethods.