Minimum Time Slots Research Articles

A Cooperative Recharging-Transmission Strategy in Powered UAV-Aided Terahertz Downlink Networks

Considering that unmanned aerial vehicles (UAVs) with the advantages of flexible deployment and high maneuverability have the limited energy to provide long-term seamless coverage, a cooperative recharging-transmission strategy is studied in this paper for the powered UAV-aided terahertz (THz) downlink networks, where a UAV-to-user THz sub-band association scheme is proposed for the THz frequency transmission to eliminate interference. Based on this, the minimum requirements of the wireless charging window and THz-transmitting window are derived. A minimization problem of minimum timeslot requirement is formulated to jointly optimize UAV placement and UAV-to-user THz sub-band association. The optimization problem is non-convex, and we propose an alternating optimization solution via iteratively solving placement subproblem and association subproblem. Specifically, we resort to the coalescent method of interior point and gradient descent algorithms to optimize UAV placement. The UAV-to-user THz sub-band association is solved as a knapsack problem by the transformation of association matrix. Simulation results validate the solution and demonstrate that the proposed strategy can achieve quasi-optimal performance compared with other contrasting strategies.

An Intelligent delay efficient data aggregation scheduling for distributed sensor networks

Data aggregation is the most prominent task in many wireless sensor network (WSN) applications, that enables all data from the network to be collected at the sink node. The most critical issue in data aggregation is data aggregation scheduling. This problem becomes even cumbersome when considered to obtain minimum latency and collision in the networks where fixed amount of data can be aggregated. Many researches have been conducted to resolve the issue of data delivery with low latency and collision. Though, some methods nearly achieved this objective but at the cost of increased complexity. Also, many works assume the system to be centralized having knowledge of every related device in the network. Practically, WSNs are likely to be distributed where each device’s information is dissociated from the other. In this context, a data aggregation scheduling algorithm is proposed to aggregate the data from a tree-based distributed sensor network. An effective aggregation tree construction based on Dijkstra’s algorithm is adopted which avoids the chance of re-transmission of data. Furthermore, a new collision prevention scheduling (CPS) algorithm is designed which ensures the data aggregation through non-collision schedules using minimum time slots. The proposed method shows 54.74% less aggregation latency compared to its competitor data aggregation scheduling approach. The outcome of extensive simulations confirms the efficiency and good performance of the proposed algorithm over previous works.

Resource allocation based on multi-grouping and frame expansion for NOMA backscatter communication network

Non-orthogonal multiple access (NOMA) and Backscatter Communication (BackCom) have great development potential in the Internet of Things (IoT). However, the power regulation and energy harvesting capacity of backscatter node (BN) in backscatter network are limited, and it is necessary to explore an appropriate resource allocation scheme to combine NOMA with BackCom. This work presents a resource allocation scheme based on multi-grouping and frame expansion to ensure reliable communication. The BNs are grouped twice to improve the total power by setting more accurate and appropriate reflection coefficients for BNs. Considering the difference of energy harvesting efficiency between BNs, different time slot lengths are set to ensure the energy supply of BNs, and the selection criterion of minimum time slot length is given. The experimental results show that the proposed scheme can effectively improve system throughput and decoding performance.

Resource scheduling based on routing tree and detection matrix for Internet of things

Effective scheduling of limited communication resources is one of the critical methods for data transmission in the Internet of things. However, the time slot utilization rate of many existing resource scheduling methods of Internet of things is not high. This article proposes a new efficient resource scheduling based on routing tree and detection matrix for Internet of things. In heterogeneous Internet of things, according to the different working modes and functions, the nodes are divided into Internet of things devices, routing nodes, and base station. We use time slot multiplexing to improve the time slot utilization of continuous transmission in Internet of things. First, the time slot allocation table in a round is obtained by the time slot scheduling based on the routing tree. Then, the collision matrix and the transmission matrix are established based on the time slot allocation table in a round. Finally, the minimum time slot scheduling in continuous rounds is determined based on the routing tree and the detection matrix. The experimental results show that the resource scheduling based on routing tree and detection matrix effectively improves the utilization of time slots and improves the throughput of the Internet of things.

Distributed Shortest Link Scheduling Algorithms With Constant Time Complexity in IoT Under Rayleigh Fading

For the shortest link scheduling (SLS), i.e., scheduling a given set of links with minimum time slots, we consider the distributed algorithm design by using the locality of the protocol model with high fidelity under the Rayleigh fading. Different from most previous works, focusing on distributed algorithm design under the deterministic SINR model, which ignores the fading effects in signal propagation, we first show that a successful link of protocol model is also feasible under the deterministic SINR model, then it can be scheduled successfully with high probability under the Rayleigh fading, by upper-bounding interference outside interference range of protocol model. Then on the basis of this key conclusion, we design LLS-SLS algorithm to solve SLS within (2eΔ max T + 1)δ log 2 Δ max T time slots for a constant δ. Specifically, Δ max T is the number of a sender's neighbors within some certain range, and can be upper-bounded. Next, based on the concept of random contention, we design CLLS algorithm to schedule all links after costing 4(δ + 1)Δ max T ln (Δ max T + 1) time slots. In addition, extensive simulations evaluate the performance of two proposed algorithms.

RFID Anti-Collision Detection Algorithm Based on Improved Adaptive N-Tree

This paper proposes a type of improved adaptive N-tree anti-collision algorithm based on the traditional one for RFID system by combination with maximum likelihood estimation and probe pre-detection. This algorithm inherits some features from Alpha- and tree-based anti-collision algorithms and effectively restrain the star-vation of the two algorithms. It has also filled in the gaps of tag collision with higher probability. The study turns out that the improved adaptive N-tree anti-collision algorithm as proposed can feature adaptive choice of the value N of the tree, length breaks of free timeslots, restraints on defects such as more tag classification and higher collision probability just as what the traditional tree-based algorithm has. N-tree built by level-to-level frame identification eliminates the free timeslots, and improves the tag identification precision for the RFID system. The results from simulation experiment reveal that the algorithm proposed in this paper has lower Error Sampling Reckon (ESR) and Throughput Rate Deviation (TRD), and features large throughput rate (87%), low delay of tag recognition and minimum timeslots, and etc. hence to be better applied in large-scale logistics and other fields where fast information recognition is involved.

A Bandwidth-Efficient MAC Scheme for Mission-Critical Applications in Industrial Wireless Sensor Networks

Industrial wireless sensor networks (IWSNs) have the potential to contribute significantly to a variety of wireless sensing endpoints, such as cable replacement, mobility, flexibility and cost reduction. However, the harsh and varied industrial environment entails addressing severe challenges, such as dust, heat, electromagnetic interference (EMI) and radio frequency interference from the other heterogeneous networks. One of the important challenges is the link burstiness in industrial wireless environments, which has not been heavily researched. In this paper, we propose a new timeslot scheduling algorithm to address this problem. The algorithm allows transmissions on the same link to be separated at least by a minimum timeslot distance. Moreover, to provide a synergistic complement to the timeslot scheduling, we also propose a timeslot reuse scheme, which facilitates improved efficiency and reliability in the bandwidth utilization and retransmission and decreases the average delay of the packet arrival. We evaluate the proposed algorithm and scheme by a real implementation, targeting a specific industrial application. The experimental results generally indicate that the proposed media access control (MAC) scheme greatly improves the reliability and decreases the packet arrival delay. Compared with the existing popular methods, the execution of our scheme indicates a minimal link burstiness influence and possesses more efficient bandwidth utilization.

Sports tournament scheduling to determine the required number of venues subject to the minimum timeslots under given formats

We studied a two-phase, preliminary and finals, tournament, which commonly adopted for non-professional sports. The round robin tournament in divisions is played in the preliminary phase, followed by one of the three variants, namely single elimination, double elimination, and round robin in the finals phase. The objective is to determine the required number of venues (tables or courts) subject to the least timeslots under the given format. We used a diagonal symmetric matrix to pair teams to games and to schedule games in timeslots for the round robin tournament. For the preliminary phase, we proposed a procedure to find the number of divisions and the number of teams in each division that minimize the total number of games and timeslots accordingly. For the finals phase, we determined the number of venues required in the least timeslots. We then formulated a constraint programming model based on the diagonal symmetric matrix for the round robin tournament. Finally, we provided suggestions for choosing the appropriate competition format.

Analysis on Energy Optimized Data Collection in Tree Based Ad-Hoc Sensor Network

Fast and energy efficient data collection in an energy constraint ad-hoc sensor network is always a challenging issue. The network topology and interferences causes significant effects on data collection and hence on sensors' energy usage. Various approaches using single channel, multichannel and convergecasting had already been proposed. Here in this paper we have shown data collection performance using multi-frequency in channel assignment, and effect of network topology, for moderate size networks of about 50-100 nodes. For the study we have used some realistic simulation models under many-to-one communication paradigm called convergecast, a single frequency channel and TDMA technique to have minimum time slots for convergecasting.

Design and Stability Analysis for Anytime Control via Stochastic Scheduling

In this paper, we consider the problem of designing controllers for linear plants to be implemented in embedded platforms under stringent real-time constraints. These include preemptive scheduling schemes, under which the execution time allowed for control software tasks is uncertain. In a conservative Hard Real-Time (HRT) design approach, only a control algorithm that (in the worst case) is executable within the minimum time slot guaranteed by the scheduler would be employed. In the spirit of modern Soft Real-Time (SRT) approaches, we consider here an "anytime control" design technique, based on a hierarchy of controllers for the same plant. Higher controllers in the hierarchy provide better closed-loop performance, while typically requiring longer execution time. Stochastic models of the scheduler and of algorithm execution times are used to infer probabilities that controllers of different complexity can be executed at different periods. We propose a strategy for choosing among executable controllers, maximizing the usage of higher controllers, which affords better exploitation of the computational platform than the HRT design while guaranteeing stability (in a suitable stochastic sense). Results on the robustness with respect to uncertainties affecting the scheduler model, and on bumpless transfer for tracking problems are also reported. Simulation results on the control of two prototypical mechanical systems show that performance is substantially enhanced by our anytime control technique w.r.t. worst case-based scheduling.

Joint Scheduling of Rate-Guaranteed and Best-Effort Users over a Wireless Fading Channel

We address multi-user scheduling over the downlink channel in wireless data systems. Specifically, we consider a time-slotted system with a single transmitter serving multiple users, where the channel condition of each user is time varying. Based on the throughput requirements, the user set is divided into two classes (i) throughput guaranteed (QoS) users, and, (ii) best effort (BE) users. For this system we obtain the optimal policy that serves the QoS users with the minimum time-slot utilization and maximizes the total fraction of time-slots allocated to the BE users. We show that the optimal policy has a simple geometric structure that can be easily visualized graphically. In the special case of Rayleigh fading, we obtain closed-form formulas that relate the achievable throughput-rate guarantee of the QoS users as a function of other system parameters, thus, providing closed-from relationships to understand the various system tradeoffs. Analytical comparison between the optimal and the random-scheduling policy shows that gains on the order of ln(N) can be achieved, where N is the number of QoS users. Finally, we present simulation results comparing the optimal policy under Rayleigh and Nakagami fading with other heuristic policies including a well known opportunistic-scheduling policy.