Vehicles on the road are expected to connect continuously to the Internet at sufficiently high speeds, e.g., several Mbps or higher, to support multimedia applications. However, even when passing through a well-facilitated city area, Internet access can be unreliable and even disconnected if the travel speed is high. We therefore propose a network path selection technique to meet network throughput requirements. The proposed technique is based on the attractor selection model and enables vehicles to switch the path from a route connecting directly to a cellular network to a relay type through neighboring vehicles for Internet access. We also develop a mechanism that prevents frequent path switching when the performance of all available paths does not meet the requirements. We conduct field evaluations by platooning two vehicles in a real-world driving environment and confirm that the proposed technique maintains the required throughput of up to 7Mbps on average. We also evaluated our proposed technique by extensive computer simulations of up to 6 vehicles in a platoon. The results show that increasing platoon length yields a greater improvement in throughput, and the mechanism we developed decreases the rate of path switching by up to 25%.

Process variation has become prominent in the advanced CMOS technology, making the timing of fabricated circuits more uncertain. In this paper, we propose a Layout-Aware Path Selection (LAPS) technique to accurately estimate the circuit timing variation from a small set of paths. Three features of paths are considered during the path selection. Experiments conducted on benchmark circuits with process variation simulated with VARIUS show that, by selecting only hundreds of paths, the fitting errors of timing distribution are kept below 5.3% when both spatial correlated and spatial uncorrelated process variations exist.

Sensor networks are often used to understand underlying phenomena that are reflected through sensing data. In real world applications, this understanding supports decision makers attempting to access a disaster area or monitor a certain event regularly and thus necessary actions can be triggered in response to the problems. Practitioners designing such systems must overcome difficulties due to the practical limitations of the data and the fidelity of a network condition. This paper explores the design of a network solution for the data acquisition domain with the goal of increasing the efficiency of data gathering efforts. An unmanned aerial vehicle (UAV) is introduced to address various real-world sensor network challenges such as limited resources, lack of real-time representative data, and mobility of a relay station. Towards this goal, we introduce a novel cooperative path selection framework to effectively collect data from multiple sensor sources. The framework consists of six main parts ranging from the system initialization to the UAV data acquisition. The UAV data acquisition is useful to increase situational awareness or used as inputs for data manipulation that support response efforts. We develop a system-based simulation that creates the representative sensor networks and uses the UAV for collecting data packets. Results using our proposed framework are analyzed and compared to existing approaches to show the efficiency of the scheme.

In the future Internet of Things/M2M network, enormous amounts of data generated from sensors must be processed and utilized by cloud applications. In recent years, sensor data stream delivery, which collects and sends sensor data periodically, has been attracting great attention. As for sensor data stream delivery, the receivers have different delivery cycle requirements depending on the applications or situations. In this paper, we propose a sensor data stream delivery method to accommodate heterogeneous cycles on the cloud. The proposed method uses distributed hashing to determine relay nodes on the cloud and construct delivery paths autonomously. We evaluate the effectiveness of the proposed method in simulations. The simulation results show that the proposed method halves the maximum load of nodes compared to the baseline methods and achieves high load balancing.

We deal with a path selection problem for heterogeneous wireless networks integrated with Frequency Agile Access Points. Our goal is to find the minimum achievable amount of radio resources required to set up a transmission path. We propose to formulate the path selection approach as a minimum cost flow problem.

Motivated by the recent research in crosslayer design of cooperative wireless network, we propose a distributed cooperative routing algorithm for a multihop multi-relay wireless network to achieve selection diversity. We propose two algorithms, rate optimal path selection and outage optimal path selection, to satisfy the different requirements of the systems. Both algorithms work on distributed processing without requiring any centralized controller. Simulations are conducted to evaluate the performance of the proposal. The results of the simulations show that the proposed routing algorithms significantly improve the end-to-end data rate and outage performance compared with noncooperative routing protocols.

Critical path selection is very important in delay testing. Critical paths found by conventional static timing analysis (STA) tools are inadequate to represent the real timing of the circuit, since neither the testability of paths nor the statistical variation of cell delays caused by process variation is considered. This paper proposed a novel path selection method considering process variation. The circuit is firstly simplified by eliminating non-critical edges under statistical timing model, and then divided into sub-circuits, while each sub-circuit has only one prime input (PI) and one prime output (PO). Critical paths are selected only in critical sub-circuits. The concept of partially critical edges (PCEs) and completely critical edges (CCEs) are introduced to speed up the path selection procedure. Two path selection strategies are also presented to search for a testable critical path set to cover all the critical edges. The experimental results showed that the proposed circuit division approach is efficient in path number reduction, and PCEs and CCEs play an important role as a guideline during path selection.

In this letter, the effect of the time difference of arrival (TDoA) on synchronous types or asynchronous types of OFDMA-based multi-hop relay (MR) systems is investigated. Signal-to-interference plus noise ratios (SINRs) for downlinks and uplinks are defined to measure the degree of interference due to TDoA in asymmetric MR systems. A path selection technique based on the SINR is then proposed to determine the optimal paths for the uplink and downlink independently. It is shown that asymmetric routing can improve the performance of OFDMA-based MR systems when the proposed technique is applied to the path selection of the uplink taking into account the effect of the TDoA.

Wireless LANs, which consist of access points and wireless stations, have widely spread in recent years. Routing in wireless LANs suffers the problem that each wireless station selects an access point and a wired path to its destination station. It is desired to design an adaptive routing protocol for wireless LANs since throughputs of communications are dynamically affected by selections of other wireless stations and external environmental changes. In this paper, we propose a routing protocol for wireless LANs based on attractor selection. Attractor selection is a biologically inspired approach, and it has high adaptability to dynamic environmental changes. By applying attractor selection, each wireless station can adaptively select its access point and wired path with high throughput against environmental changes. In addition, we design the protocol with a new technique: combination of multiple attractor selections. The technique is useful because it enables us to divide a problem into several simpler problems. To the best of our knowledge, our protocol is the first one designed around a combination of multiple attractor selections. We show the effectiveness and adaptability of our protocol by simulations.

Various types of data from environment are used to provide user-adaptive services. Among them, data of a user's past moving paths are useful to predict a moving user's next location and provide related services. This paper proposes a method to predict a moving user's location through analyzing his/her past moving paths. This method analyzes the user's moving path by using three elements of distance, time and direction of moving paths and Dynamic Time Warping (DTW), and selects the representative path, which is the one most similar to the current moving path in the past paths. The selected path can be used to provide service like space and time estimation.

In future high-speed networks, provision of diverse multimedia services with strict quality-of-service (QoS) requirements, such as bandwidth, delay and so on, is desired. QoS routing is a possible solution to handle these services. Generally, a path selection for QoS routing is formulated as a shortest path problem subject to multiple constraints. However, it is known to be NP-complete when more than one QoS constraint is imposed. As a result, many heuristic algorithms have been proposed so far. The authors proposed a path selection algorithm Fallback+ for QoS routing, which focuses not only on the path selection with multiple constraints but also on the efficient use of network resources. This paper proposes an enhanced version of Fallback+, named Enhanced Fallback+, where in a shrewd way, it keeps tentative paths produced in the conventional Fallback algorithm with Dijkstra's algorithm. Simulation experiments prove the excellent performance of Enhanced Fallback+, compared with the original Fallback+ and other existing path selection algorithms.

This paper proposes the constraint availability and bandwidth shortest path (CABSP) selection algorithm and the extension of the adaptive modulation scheme to the CABSP (CABSP-AM) selection algorithm in the millimeter-wave (MMW) broadband entrance network for wireless heterogeneous systems. The CABSP algorithm considers the availability denoted as the quality of the MMW which is severely affected by the rainfall. The CABSP-AM algorithm, moreover, is proposed to further make more efficient use of bandwidth resources by considering the QoS requirements of each class of service in multimedia communication. As the results, the CABSP algorithm yields higher throughput performance than the conventional constraint shortest path (CSP) selection algorithm, but lower than the CABSP-AM algorithm. The spectrum efficiency improvements of the CABSP-AM over the CABSP are about 1.36 and 1.48 fold in case of error sensitive and non-sensitive classes respectively.

Since a logic circuit often has too many paths to test delay of all paths, it is necessary for path delay testing to limit the number of paths to be tested. The paths to be tested should have large delay because such paths more likely cause a fault. Additionally, a test set for the paths are required to detect other models of faults as many as possible. In this paper, we investigate two typical criteria of path selection for path delay testing. From our experiments, we observe that test patterns for the longest paths cannot cover many local delay defects such as transition faults.

This paper proposes a disjoint path selection scheme for Generalized Multi-Protocol Label Switching (GMPLS) networks with Shared Risk Link Group (SRLG) constraints. It is called the weighted-SRLG (WSRLG) scheme. It treats the total number of SRLG members related to a link as part of the link cost when the k-shortest path algorithm is executed. In WSRLG, a link that has many SRLG members is rarely selected as the shortest path. Simulation results show that WSRLG finds more disjoint paths than the conventional k-shortest path algorithm. In addition, since WSRLG searches for the weight of the SRLG factor by using a modified binary search algorithm while satisfying the required number of disjoint paths between source and destination nodes, it can find cost-effective disjoint paths.

This paper presents a practical fault model for delay testing, called a multiple-threshold gate-delay fault model, to obtain high quality tests that guarantee the detection of delay faults for various extra-delays. Fault efficiencies for multiple thresholds of the extra-delay are introduced as a coverage metric that describes the quality of tests. Our approach guarantees that each gate-delay fault is tested on the path that is almost the longest one passing through the faulty line by using two-pattern tests with pattern-independent timing. We present the procedures of the path selection, fault simulation, and the test generation, where the path-status graph technique is used as not to rely on the enumeration of paths. Experimental results for benchmark circuits demonstrate that the proposed metric gives useful information that transition fault efficiency cannot, and that the proposed test generation can achieve high fault efficiencies for multiple-threshold gate-delay faults.

We propose a new QOS routing algorithm for finding a path that guarantees several quality of service (QOS) parameters requested by users, for ATM networks. It is known that a routing problem is NP-complete, if the number of additive QOS parameters, such as delay and cost, are more than or equal to two. Although a number of heuristic algorithms have been proposed recently to solve this problem, the appropriate choice of routing algorithms is still an open issue. In this paper, we propose a new heuristic routing algorithm, while being compliant with PNNI routing and signaling specification in the ATM Forum. The performance of algorithms is evaluated by simulation with a various network topologies and loading scenarios. This simulation results demonstrate that the proposed scheme improves the performance while reducing computational complexity.