Yean-Fu Wen

Hybrid wireless network protocols

Basically, there are two types of wireless network systems - base-station (BS) oriented networks and ad hoc wireless networks. In the first type, the mobile hosts communicate with base stations, while, in ad hoc networks, the mobile hosts communicate with one another directly. The BS-oriented wireless network has better performance and is more reliable. However, the ad hoc network topology is desirable because of its low cost, plug-and-play convenience, and flexibility. Its usage of bandwidth and battery power is more efficient, but route and communication connectivity is fairly weak; any migration by a host participating in one or more routes could make the route invalid. Much cost is incurred in maintaining communication. Thus, the ad hoc wireless network is only suitable for applications in a small geographical area. We propose hybrid wireless network protocols to combine the advantages of BS-oriented and ad hoc wireless networks. We allow two mobile hosts to communicate directly (one-hop direct transmission) or through another mobile host (two-hop direct transmission) within a BS-oriented network. The hybrid protocols are more flexible, reliable, and have better performance than the traditional protocols. Simulation results show that two-hop direct-transmission has a lower non-completion probability. If the communicating parties are always within a two-hop direct-transmission area, the rate of complete communication improves by about 20%.

Multirate Throughput Optimization With Fairness Constraints in Wireless Local Area Networks

In 802.11-based wireless local area networks (WLANs), it is difficult to simultaneously attain both high throughput and fairness for multirate traffic. There is a performance anomaly when there are stations whose data rates are much lower than the other stations, in which the aggregate throughput of the high-rate stations drastically degrades. The problem of maximizing the total throughput while maintaining time fairness among the competing stations was studied previously by the same authors. However, our previous solution sacrificed the throughput of low-rate stations. In this paper, we extend our previous work by solving the same optimization problem while maintaining both time fairness and throughput fairness. The optimization problem is formulated as a mixed-integer nonlinear programming problem. The two fairness constraints are maintained by means of changing the channel access probability and transmission time among the competing stations, which can be realized by adjusting their minimum contention window sizes and medium access control (MAC) frame sizes, respectively. A penalty function accompanied with a gradient-based approach is used to solve the problem, and its effectiveness is verified by computational experiments. The proposed solution is also compared with our previous solution in terms of convergence speed and total throughput.

On QoS Routing in Wireless Ad-Hoc Cognitive Radio Networks

Cognitive radio network (CRN) is designed to improve the low resource utilization problem caused by the fixed spectrum allocation policy used today. In CRNs, secondary users (SUs) sense spectrum holes and adaptively use the frequency band. In this paper, we tackle the Quality of Service (QoS) routing problem in wireless ad hoc CRNs. We consider such factors as available time, frequency bands, transmission range, error rate, primary user (PU) interruption rate and transmission range, and design a new QoS routing metric for wireless ad hoc CRNs. We then evaluate the performance via simulations in terms of the average and maximum end-to-end delays. The results show that our proposed metric outperforms existing solutions, including probability based, bit-rate based, and hop-count based methods.

Minimum power multicast algorithms for wireless networks with a Lagrangian relaxation approach

Energy efficiency is crucial to the implementation of broadcast and multicast services in wireless ad hoc and sensor networks. This paper proposes a path-based power-efficient approach that minimizes energy consumption in the network by optimizing the transmission ranges of all nodes. Unlike existing link-based and node-based solutions, the proposed approach, which is applicable to both static and mobile wireless networks, constructs minimum-power broadcast trees. This study uses Lagrangian Relaxation (LR) to decompose the tree-construction problem, which is NP-complete, into multiple independently solvable sub-problems. The resulting Lagrange dual solution ensures a lower bound on the objective function value. The proposed approximation heuristic solves the primal problem by obtaining the upper bound of the objective value based on the information from the set of Lagrange multipliers. This study develops a decentralized, near-optimal algorithm to solve the problem. Simulation results show that in randomly generated networks, the proposed method outperforms the existing Minimum Shortest Path Tree (MSPT) algorithm, Prim’s Minimum Spanning Tree (PMST) algorithm, and the Broadcast Incremental Power (BIP) algorithm by 30, 10, and 5%, respectively.

Multi-sink data aggregation routing and scheduling with dynamic radii in WSNs

In wireless sensor networks (WSNs) with multiple sink nodes, energy is wasted on idle listening, redundant transmissions, and unnecessary power consumption. The total energy consumption may be minimized by properly scheduling communications in conjunction with aggregating data and dynamically adjusting radii. We propose near-optimal data aggregation routing and duty cycle scheduling heuristics, denoted by MDAR and O-MAC, which achieve energy efficiency and bound latency within a reasonable range. These heuristics outperform other general data aggregation routing heuristics (e.g., CNS, GIT, and SPT) and scheduling protocols (e.g., S-MAC and T-MAC) by 7%-45%, according to our experimental results.

Optimal energy-efficient routing for wireless sensor networks

The network lifetime for wireless sensor network plays an important role to survivability. Thus, we indicate the importance of routing protocol to network lifetime, and model the expected retransmission time as a convex function with respect to aggregate flow on each sensor node. Thus we formulate the optimal energy-efficient routing as a non-linear min-max programming problem with convex product form, which can be optimally solved by optimal routing framework. Based on the optimal routing framework, we propose Lagrangean-based algorithm and primal optimal algorithm. By the combination of these two algorithms, we can optimally and efficiently get the routing assignment to maximize the network life in the sensor network. From experiments, we observe that when the optimal network lifetime increases as the number of sensor nodes increase. While the shortest path-based heuristic algorithm can only achieve about 48% network lifetime compared to our solution approach.

Energy efficiency heterogeneous wireless access selection for multiple types of applications

Modelling energy efficiency, application and state transition of network operation.Describe the problem by a mixed?integer non?linear mathematical formulation.Propose BS selection schemes based on the features of Apps and wireless networks.Compare the evaluation results with the standard scheme and discuss our findings. Mobile terminal (MT) users run various types of applications, such as e-mail, APPs, web browsers, and multimedia, through various types of wireless networks. Extending the battery life of MT, which requires a large amount of electricity for wireless transmission, has become critical. This study focused on the energy efficiency of wireless networks, such as 3G, 4G and Wi-Fi, based on application characteristics and transmission loads. The various applications are classified into idle-bound applications (e.g., e-mail service) and transmission-bound applications (e.g., multimedia) that require diverse types of wireless networks. The operation state of a wireless network includes transmitting, receiving, listening, and sleeping modes. According to the game theory of the energy consumption analysis between the characteristics of applications and wireless networks, three wireless network selection schemes IBLB (idle-bound with load-balancing), TBLB (transmission-bound with load balancing), and WLAT (weighted load and application type) were proposed to reduce the amount of power consumption. Previous studies were compared with the proposed schemes through (1) variation of the number of running applications, (2) various numbers of 3G/4G base stations and Wi-Fi access points, and (3) the combinations of various types of applications to evaluate the energy efficiency of Wi-Fi and 3G/4G access networks selections. Display Omitted

Load balancing consideration of both transmission and process responding time for multi-task assignment

The existing load balancing research mainly the unilateral fairness of the transmission network or only stand for the processing host to handle fairness issue. This work addresses the load balancing between network and host to assign tasks to the related hosts along the path with minimal processing and transmission delays subject to the capacity of processing hosts and transmission links. Three task schedulers: first-come-first-service (FCFS), minimum task assign to minimum completion time (Min-Min), and the proposed minimised the maximal process and transmission time (Min-Max) allocation mechanisms, are adopted along with biased random sampling (BRS) mechanism to observe the distribution of interactive results. This study changes three variables manipulated with the number of hosts, the number of tasks, and the expected processing time and records the maximal/average responding time and fairness index, to analyse the load balancing results. The results show that the Min-Max and BRS of the match that is used to obtain the lowest responding time to satisfy the requirement of users.

Energy-Efficient Data Aggregation Routing and Duty-Cycle Scheduling in Cluster-Based Sensor Networks

The lifetime of a network, dependent upon battery capacity and energy consumption efficiency, plays an important role in wireless sensor networks. In this paper, the reduction of energy consumption is investigated by the considerations of the effects of cluster-based data aggregation routing in conjunction with well-scheduled and dynamic power range. Modeling power consumption as a mixed integer- and nonlinear-programming problem, the objective function provides the basis by which the total energy consumption is minimized. The problem of cluster construction and data aggregation trees were proven NP- complete. Thus, we proposed heuristics for cluster construction (i.e., AvgEnergy and MaxNumS) and data aggregation routing (i.e., CDAR). We also propose a duty cycle scheduling scheme and dynamic radius to ensure the total energy consumption is minimized. The experimental results show that the heuristic proposed above outperforms other modified existing algorithms.

An Efficient Object Tracking Algorithm in Wireless Sensor Networks

In this paper, we develop a heuristic algorithm to construct an efficient object tracking in wireless sensor networks (WSNs). Such wireless sensor network has to be designed to achieve efficient object tracking for given arbitrary topology of wireless sensor networks. We consider the two-way object moving frequency of each pair of sensor nodes and link transmission cost. This problem is formulated as 0/1 integerprogramming problem. A Lagrangean Relaxationbased (LR-based) heuristic algorithm is proposed for solving the optimization problem. The experimental results showed that the proposed algorithm gets a near optimization in the efficient object tracking. Furthermore, the algorithm is very efficient and scalable in terms of the solution time.