To meet the ever-increasing demand for information technology (IT) workforce, we must educate and produce high-quality graduates. It is crucial to balance fundamental programming concepts and coding skills to develop skilled IT work forces who solve a complicated real-life problem using technology. In this project, we created scenario-based active learning modules by using a visual platform to improve student learning on programming concepts and skills.

Tracking human motion with multiple body sensors has the potential to promote a large number of applications such as detecting patient motion, and monitoring for home-based applications. With multiple sensors, the tracking system architecture and data processing cannot perform the expected outcomes because of the limitations of data association. For the collaborative and intelligent applications of motion tracking (Polhemus Liberty AC magnetic tracker), we propose a human motion tracking system with multichannel interacting multiple model estimator (MC-IMME). To figure out interactive relationships among distributed sensors, we used a Gaussian mixture model (GMM) for clustering. With a collaborative grouping method based on GMM and expectation-maximization algorithm for distributed sensors, we can estimate the interactive relationship with multiple body sensors and achieve the efficient target estimation to employ a tracking relationship within a cluster. Using multiple models with filter divergence, the proposed MC-IMME can achieve the efficient estimation of the measurement and the velocity from measured datasets of human sensory data. We have newly developed MC-IMME to improve overall performance with a Markov switch probability and a proper grouping method. The experiment results shows that the prediction overshoot error can be improved on average by 19.31% by employing a tracking relationship.

Purpose One-time password systems provide great strengths over conventional password systems: protection against over-the-shoulder, eavesdropping, replay, etc. The Grid Data Security authentication system is a server-challenge-based system. It has advantages over other one-time password systems since it does not require pre-installed software nor special devices to carry on. However, there are some weaknesses. The purpose of this paper is to analyze the weaknesses of the one-time password system and provide practical guidelines for using the one-time password system. Design/methodology/approach This paper statistically analyzes the weakness of the Grid Data Security authentication system and simulates attacks to the system to confirm the discovered weakness. The paper also suggests ways to reduce the discovered vulnerability using mathematical formula and offers practical guideline for using the system. It also identifies the system's strength on access authentication on mobile communication. Findings The Grid Data Security authentication system which is a server-challenge-based one-time password system has a great weakness when an attacker gains its user-interface screen and its GridCode. The discovered vulnerability can be improved by changing cardinality of the GridCode. This paper creates a formula that can help a system manager to decide the security level and its required cardinality of GridCode and length of password. It also identifies the system's strengths on mobile communication. Originality/value The paper provides a practical tool for security managers to identify requirements of cardinality of GridCode and password length for certain levels of security.

Achieving accurate and efficient fault localization in large transparent all-optical networks (TONs) is an important and challenging problem due to unique fault-propagation, time constraints, and scalability requirements. In this paper, we introduce a novel technique for optimizing the speed of fault-localization through the selection of an active set of monitors for centralized and hierarchically-distributed management. The proposed technique is capable of providing multiple levels of fault-localization-granularity, from individual discrete optical components to the entire monitoring domains. We formulate and prove the NP-completeness of the optimal monitor activation problem and present its Integer Linear Program (ILP) formulation. Furthermore, we propose a novel heuristic whose solution quality is verified by comparing it with an ILP. Extensive simulation results provide supporting analysis and comparisons of achievable alarm-vector reduction, localization coverage, and time complexity, for flat and hierarchically distributed monitoring approaches. The impact of network connectivity on fault localization complexity in randomly generated topologies is also studied. Results demonstrate the effectiveness of the proposed technique in efficient and scalable monitoring of transparent optical networks.

Rapid fault identification and localization in optical networks are crucial due to high data rates. These problems are more challenging than in traditional electronic networks because of optical transparency. In a transparent optical network which does not regenerate optical signals, a fault may propagate to various parts of the network from the origin, and multiple alarms can be generated for a single failure. In order to reduce the number of redundant alarms, simplify fault localization, and reduce the fault localization time, the number and location of fault monitors that are turned on should be optimized for a given network. In this paper, we formulate a problem on the optimal activation of network monitoring devices and propose a solution approach. First, we provide a brief summary of available physical-layer monitoring devices, and then present a scheme for optimal monitor activation. We show the NP-completeness of the problem and present a mixed-integer-linear-program (MILP) formulation of it. We also present a heuristic, whose performance is evaluated through comparisons with the solutions to the MILP, as well as a naive monitor activation approach.

Multicast based video conferencing in wireless networks is recently receiving more and more attention. In this paper, we propose a novel linker-level protocol, multicast with orthogonal CTS (MOCTS) protocol, to provide efficient wireless multicast. Our approach uses orthogonal Walsh code to modulate CTS packets at different receiving nodes. The modulated CTSs are simultaneously transmitted and decoded at the source node, thus considerably reducing multicast CTS collisions. Simulation results show that the MOCTS protocol can reduce more than 20% in total transmission efforts

We investigate a unique scheduling problem in wireless sensor networks where all nodes in a cluster send exactly one packet to a designated sink node with goal of minimized transmission time. The difficulty lies in the fact that node transmissions must be sufficiently isolated either in time or in space to avoid collisions. The problem is formulated and solved via graph representation. We prove that with specific network topologies (either line or tree); an optimal transmission schedule can be obtained efficiently through a pipeline-like schedule. The minimum time required for a line (or tree) topology with n nodes is 3(n-2). We further prove that our scheduling problem is NP-hard for general graphs. We propose a heuristic algorithm for general graphs. Our heuristic tries to schedule as many independent segments as possible to increase the degree of parallel transmission. This algorithm is compared to an RTS/CTS based distributed algorithm. Preliminary simulated results indicate that our heuristic algorithm out-performs the RTS/CTS based distributed algorithm (up to 30%) and exhibits stable scheduling behavior.

Summary form only given. As the energy consumption in wireless sensor nodes is dominated by the radio transmission circuitry, the network configuration must be designed to minimize the power consumption by transmission radios. Sensor nodes are generally equipped with short-range radios that require low power consumption. But the current technology allows each node to adjust its transmission power. We consider the dual power radios in which the radio of each node can be assigned high-or low-power during the network initializing stage. Our primary goal in such an assignment is to minimize the overall power consumption by radios to maximize the network lifetime while maintaining the full network connectivity, the most fundamental network functionality. Using a graph-theoretic approach, we formulate the problem as a "minimum subgraph" problem, show its NP-completeness, establish upper and lower bounds on the optimum solution, and present a near-optimal heuristic algorithm and simulation results.

Network survivability is a crucial requirement in high-speed optical networks. Typical approaches of providing survivability have considered the failure of a single component such as a link or a node. We motivate the need for considering double-link failures and present three loopback methods for handling such failures. In the first two methods, two edge-disjoint backup paths are computed for each link for rerouting traffic when a pair of links fails. These methods require the identification of the failed links before recovery can be completed. The third method requires the precomputation of a single backup path and does not require link identification before recovery. An algorithm that precomputes backup paths for links in order to tolerate double-link failures is then presented. Numerical results comparing the performance of our algorithm with other approaches suggest that it is possible to achieve almost 100% recovery from double-link failures with a moderate increase in backup capacity. A remarkable feature of our approach is that it is possible to trade off capacity for restorability by choosing a subset of double-link failures and designing backup paths using our algorithm for only those failure scenarios.

Network survivability is a crucial requirement in high-speed optical networks. Typical approaches of providing survivability have considered the failure of a single component such as a link or a node. We consider a failure model in which any two links in the network may fail in an arbitrary order. Three loopback methods of recovering from double-link failures are presented. The first two methods require the identification of the failed links, while the third one does not. However, precomputing the backup paths for the third method is more difficult than for the first two. A heuristic algorithm that pre-computes backup paths for links is presented. Numerical results comparing the performance of our algorithm with other approaches suggests that it is possible to achieve 100% recovery from double-link failures with a modest increase in backup capacity.

This paper considers the transmission of uniform deterministic traffic in an optical broadcast-star network using wavelength division multiplexing. Lower bounds are established on the minimum time to exchange information between every node pair in such a network with tunable transmitters and fixed-tuned receivers. Three different scheduling algorithms are developed that are strictly optimal in three regimes of system parameters. The results are applicable to arbitrary tuning delays and arbitrary numbers of wavelength channels, and indicate the existence of a well-defined transition regime from tuning-limited operation to bandwidth-limited operation.

All-optical networks (AONs) with a broadcast-star based physical topology offer the possibility of transmission scheduling to resolve channel and receiver conflicts. This paper considers the problem of scheduling packet transmissions in a wavelength-division multiplexed (WDM) optical network with tunable transmitters and fixed-tuned receivers. The scheduling problem is complicated by tuning latency, a limited number of channels, and arbitrary traffic demands. We first analyze scheduling all-to-all packet transmissions and obtain a new lower bound for the schedule length. The lower bound is achieved by an algorithm proposed by Pieris and Sasaki (1994). We then extend the analysis to the case of arbitrary traffic demands and obtain lower bounds for the schedule length. Two constructions for scheduling algorithms are provided through list scheduling and multigraphs. The upper bounds so obtained not only provide performance guarantees with arbitrary demands, but also nearly meet the lower bound in simulations.