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Algorithms for scheduling TDMA transmissions in multi-hop networks usually determine the smallest length conflict-free assignment of slots in which each link or node is activated at least once. This is based on the assumption that there are many independent point-to-point flows in the network. In sensor networks however often data are transferred from the sensor nodes to a few central data collectors. The scheduling problem is therefore to determine the smallest length conflict-free assignment of slots during which the packets generated at each node reach their destination. The conflicting node transmissions are determined based on an interference graph, which may be different from connectivity graph due to the broadcast nature of wireless transmissions. We show that this problem is NP-complete. We first propose two centralized heuristic algorithms: one based on direct scheduling of the nodes or node-based scheduling, which is adapted from classical multi-hop scheduling algorithms for general ad hoc networks, and the other based on scheduling the levels in the routing tree before scheduling the nodes or level-based scheduling, which is a novel scheduling algorithm for many-to-one communication in sensor networks. The performance of these algorithms depends on the distribution of the nodes across the levels. We then propose a distributed algorithm based on the distributed coloring of the nodes, that increases the delay by a factor of 10–70 over centralized algorithms for 1000 nodes. We also obtain upper bound for these schedules as a function of the total number of packets generated in the network.

The efficient operation of airports, and runways in particular, is critical to the throughput of the air transportation system as a whole. Scheduling arrivals and departures at runways is a complex problem that needs to address diverse and often competing considerations of efficiency, safety, and equity among airlines. One approach to runway scheduling that arises from operational and fairness considerations is that of constrained position shifting (CPS), which requires that an aircraft's position in the optimized sequence not deviate significantly from its position in the first-come-first-served sequence. This paper presents a class of scalable dynamic programming algorithms for runway scheduling under constrained position shifting and other system constraints. The results from a prototype implementation, which is fast enough to be used in real time, are also presented.

Wireless sensor networks (WSNs) have been widely used in industrial systems. Their real-time performance and reliability are fundamental to industrial production. Many works have studied the two aspects, but only focus on single criticality WSNs. Mixed criticality requirements exist in many advanced applications in which different data flows have different levels of importance (or criticality). In this paper, first, we propose a scheduling algorithm, which guarantees the real-time performance and reliability requirements of data flows with different levels of criticality. The algorithm supports centralized optimization and adaptive adjustment. It is able to improve both the scheduling performance and flexibility. Then, we provide the schedulability test through rigorous theoretical analysis. We conduct extensive simulations, and the results demonstrate that the proposed scheduling algorithm and analysis significantly outperform existing ones.

TSCH is one of the access behavior modes defined in the IEEE 802.15.4e standard. It combines time slotted access with multi-channel and channel hopping capabilities. TSCH is a trend used as the underlying architecture of the Internet of Things. However, IEEE 802.15.4e defines when the MAC executes a schedule but it does not specify how the schedule is built. This paper focuses on the problem of data transmission scheduling for TSCH network which uses the IEEE802 .15.4e TSCH as the MAC protocol. We adopt matching rule to resolve conflicts in the TSH network and matching scheduling algorithm(MSA) to solve the problem of communication resources allocation in tree topology. The scheduling algorithm MSA can avoid conflict, reduce the delay and energy consumption. OSA is proposed by further optimization of MSA. Through simulation experiments, the proposed method can effectively shorten the time delay, reduce the energy consumption and reduce the utilization rate of the channel.

The conventional enterprise accounting information resource sharing model has the problem of fuzzy accounting information characteristics, resulting in low schedulability. An agricultural enterprise accounting information resource sharing model based on big data technology is designed. Obtain the goal of agricultural enterprise business process reengineering, establish the standard process of mutual integration of enterprise accounting information, combined with the principle of data mining, extract the characteristics of accounting information by using big data technology, divide the spectrum module according to the deployment density of small cells, design the heterogeneous wireless network resource management model, optimize the resource distribution level, and construct the resource sharing model by using hierarchical scheduling algorithm. Experimental results: the mean schedulability rates of the enterprise accounting information resource sharing model and the other two models are 60.073%, 49.801% and 49.319%, which proves that the enterprise accounting information resource sharing model integrating big data technology has more advantages.

In cloud computing, some large tasks may occupy too many resources and some small tasks may wait for a long time based on First-In-First-Out (FIFO) scheduling algorithm. To reduce tasks’ waiting time, we propose a task scheduling algorithm based on fuzzy clustering algorithms. We construct a task model, resource model, and analyze tasks’ preference, then classify resources with fuzzy clustering algorithms. Based on the parameters of cloud tasks, the algorithm will calculate resource expectation and assign tasks to different resource clusters, so the complexity of resource selection will be decreased. As a result, the algorithm will reduce tasks’ waiting time and improve the resource utilization. The experiment results show that the proposed algorithm shortens the execution time of tasks and increases the resource utilization.

Scheduling algorithms play an important role for TDMA-based wireless sensor networks. Existing TDMA scheduling algorithms address a multitude of objectives. However, their adaptation to the dynamics of a realistic wireless sensor network has not been investigated in a satisfactory manner. This is a key issue considering the challenges within industrial applications for wireless sensor networks, given the time-constraints and harsh environments. In response to those challenges, we present SAS-TDMA, a source-aware scheduling algorithm. It is a cross-layer solution which adapts itself to network dynamics. It realizes a trade-off between scheduling length and its configurational overhead incurred by rapid responses to routes changes. We implemented a TDMA stack instead of the default CSMA stack and introduced a cross-layer for scheduling in TOSSIM, the TinyOS simulator. Numerical results show that SAS-TDMA improves the quality of service for the entire network. It achieves significant improvements for realistic dynamic wireless sensor networks when compared to existing scheduling algorithms with the aim to minimize latency for real-time communication.

We propose a new framework for the (length and reliability) bicriteria static multiprocessor scheduling problem. Our first criterion remains the schedule's length, which is crucial to assess the system's real-time property. For our second criterion, we consider the global system failure rate, seen as if the whole system were a single task scheduled onto a single processor, instead of the usual reliability, because it does not depend on the schedule length like the reliability does (due to its computation in the classical exponential distribution model). Therefore, we control better the replication factor of each individual task of the dependency task graph given as a specification, with respect to the desired failure rate. To solve this bicriteria optimization problem, we take the failure rate as a constraint, and we minimize the schedule length. We are thus able to produce, for a given dependency task graph and multiprocessor architecture, a Pareto curve of nondominated solutions, among which the user can choose the compromise that fits his or her requirements best. Compared to the other bicriteria (length and reliability) scheduling algorithms found in the literature, the algorithm we present here is the first able to improve significantly the reliability, by several orders of magnitude, making it suitable to safety-critical systems.

High data transmission efficiency is a key requirement for an ultrasonic phased array with multi-group ultrasonic sensors. Here, a novel FIFOs scheduling algorithm was proposed and the data transmission efficiency with hardware technology was improved. This algorithm includes FIFOs as caches for the ultrasonic scanning data obtained from the sensors with the output data in a bandwidth-sharing way, on the basis of which an optimal length ratio of all the FIFOs is achieved, allowing the reading operations to be switched among all the FIFOs without time slot waiting. Therefore, this algorithm enhances the utilization ratio of the reading bandwidth resources so as to obtain higher efficiency than the traditional scheduling algorithms. The reliability and validity of the algorithm are substantiated after its implementation in the field programmable gate array (FPGA) technology, and the bandwidth utilization ratio and the real-time performance of the ultrasonic phased array are enhanced.

The rapid development of wireless sensor networks motivates the researchers and industries to implement large scale wireless sensor network in highly sensitive applications. Since the data aggregation is the major functionality of the wireless sensor network, the network implementation should avoid data aggregation issues like energy, collision, delay and security. As sensor nodes are deployed in hostile environments, the security of the sensitive information such as authenticity, confidentiality and integrity should be considered. To provide a unique solution that resolve the security and energy issues, this paper proposes a hybrid secure data aggregation (HSDA) to provide high secure data aggregation in an energy efficient way. HSDA implements an end to end symmetric key cryptography for secure authentication using shared public key and it uses hop by hop asymmetric key cryptography with the private keys of each node for data integrity and confidentiality. The proposed model performs the private key generation and encryption at the leaf node to reduce the communication and computation overhead of the sensor nodes. The proposed energy efficient way for achieving the secure data aggregation is proved through simulation results. Compared with existing models, the proposed model provides a new solution that resolves energy as well as security issues in data aggregation.