scholarly journals An Efficient Algorithm to Find Broadcast Schedule in Ad Hoc TDMA Networks

2008 ◽  
Vol 2008 ◽  
pp. 1-10 ◽  
Author(s):  
Imtiaz Ahmad ◽  
Buthaina Al-Kazemi ◽  
A. Shoba Das
Keyword(s):  
Network Performance ◽  
Ad Hoc ◽  
Heuristic Algorithms ◽  
Solution Space ◽  
Search Space ◽  
Minimum Length ◽  
Scheduling Problem ◽  
Broadcast Scheduling ◽  
Practical Concern ◽  
Broadcast Schedule

The broadcast scheduling is of fundamental importance and practical concern for ad hoc network performance measures such as the communication delay and the throughput. The scheduling problem on hand involves determination of a collision-free broadcast schedule with the minimum length TDMA frame and the maximum slot utilization by efficient distribution of slots among stations. The problem is widely known as NP-complete, and diverse heuristic algorithms were reported to solve this problem recently. The intractable nature of the broadcast scheduling problem and its importance in ad hoc TDMA networks necessitates development of more efficient heuristic algorithms. In this paper, we developed a new heuristic approach which employs a tight lower bound derived from the maximal incompatibles and generates a search space from the set of maximal compatibles. The developed algorithm is very efficient and effective in conquering the intractable nature of the broadcast scheduling problem in the sense that it explores complex solution space in smaller CPU time. A comparison with existing techniques for the test examples reported in the literature shows that our algorithm achieves a collision-free broadcast with minimum frame length and the maximum slot utilization in relatively shorter time.

scholarly journals QoS Routing in Ad-Hoc Networks Using GA and Multi-Objective Optimization

2011 ◽  
Vol 7 (3) ◽  
pp. 169-188 ◽  
Author(s):  
Admir Barolli ◽  
Evjola Spaho ◽  
Leonard Barolli ◽  
Fatos Xhafa ◽  
Makoto Takizawa
Keyword(s):  
Ad Hoc Networks ◽  
Ad Hoc ◽  
Heuristic Algorithms ◽  
Routing Algorithm ◽  
Genetic Load ◽  
Search Space ◽  
Qos Routing ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Hoc Networks

Much work has been done on routing in Ad-hoc networks, but the proposed routing solutions only deal with the best effort data traffic. Connections with Quality of Service (QoS) requirements, such as voice channels with delay and bandwidth constraints, are not supported. The QoS routing has been receiving increasingly intensive attention, but searching for the shortest path with many metrics is an NP-complete problem. For this reason, approximated solutions and heuristic algorithms should be developed for multi-path constraints QoS routing. Also, the routing methods should be adaptive, flexible, and intelligent. In this paper, we use Genetic Algorithms (GAs) and multi-objective optimization for QoS routing in Ad-hoc Networks. In order to reduce the search space of GA, we implemented a search space reduction algorithm, which reduces the search space for GAMAN (GA-based routing algorithm for Mobile Ad-hoc Networks) to find a new route. We evaluate the performance of GAMAN by computer simulations and show that GAMAN has better behaviour than GLBR (Genetic Load Balancing Routing).

scholarly journals Limited Search Space-Based Algorithm for Dual Resource Constrained Scheduling Problem with Multilevel Product Structure

2019 ◽  
Vol 9 (19) ◽  
pp. 4005 ◽  
Author(s):  
Geunho Yang ◽  
Byung Do Chung ◽  
Sang Jin Lee
Keyword(s):  
Genetic Algorithm ◽  
Job Shop ◽  
Hybrid Genetic Algorithm ◽  
Optimal Solution ◽  
Solution Space ◽  
Search Space ◽  
Product Structure ◽  
Neighborhood Search ◽  
Scheduling Problem ◽  
Resource Constrained

This study addresses the dual resource constrained flexible job shop scheduling problem (DRCFJSP) with a multilevel product structure. The DRCFJSP is a strong NP-hard problem, and an efficient algorithm is essential for DRCFJSP. In this study, we propose an algorithm for the DRCFJSP with a multilevel product structure to minimize the lateness, makespan, and deviation of the workload with preemptive priorities. To efficiently solve the problem within a limited time, the search space is limited based on the possible start and end time, and focus is placed on the intensification rather than diversification, which can help the algorithm spend more time to find an optimal solution in a reasonable solution space. The performance of the proposed algorithm is compared with those of a genetic algorithm and a hybrid genetic algorithm with variable neighborhood search. The numerical experiments demonstrate that the strategy limiting the search space is effective for large and complex problems.

A Search Space Reduction Algorithm for Improving the Performance of a GA-Based QoS Routing Method in Ad-Hoc Networks

2007 ◽  
Vol 3 (1) ◽  
pp. 41-57 ◽  
Author(s):  
Leonard Barolli ◽  
Makoto Ikeda ◽  
Giuseppe De Marco ◽  
Arjan Durresi ◽  
Akio Koyama ◽  
...  
Keyword(s):  
Ad Hoc Networks ◽  
Ad Hoc ◽  
Heuristic Algorithms ◽  
Search Space ◽  
Qos Routing ◽  
Routing Algorithms ◽  
Data Traffic ◽  
Space Reduction ◽  
Routing Method ◽  
Hoc Networks

A lot of work has been done on routing in MANETs. However, the proposed routing solutions deal only with the best effort data traffic. Connections with Quality of Service (QoS) requirements are not supported. The QoS routing has been receiving increasingly intensive attention in the wireline network domain. However, for MANETs only few QoS routing algorithms are proposed. For MANETs, approximated solutions and heuristic algorithms should be developed and QoS routing algorithms should be adaptive, flexible, and intelligent. In our previous work, we proposed a Genetic Algorithm (GA) based routing method for Mobile Ad-hoc Networks (GAMAN). In this paper, we enhance the proposed algorithm by adding an effective topology extraction algorithm to reduce the search space of GAMAN. We call this algorithm E-GAMAN. The E-GAMAN uses two QoS parameters for routing. The performance evaluation via simulations show that E-GAMAN has a good performance.

scholarly journals Bio-Inspired Workflow Scheduling on HPC Platforms

2021 ◽  
Vol 15 (1) ◽  
pp. 60-68
Author(s):  
Mandeep Kaur ◽  
Sanjay Kadam
Keyword(s):  
Heuristic Algorithms ◽  
Research Work ◽  
Hybrid Approach ◽  
Optimal Schedule ◽  
Solution Space ◽  
Scheduling Algorithms ◽  
Search Space ◽  
Use Of Resources ◽  
Grid Applications ◽  
Bacteria Foraging Optimization Algorithm

Efficient scheduling of tasks in workflows of cloud or grid applications is a key to achieving better utilization of resources as well as timely completion of the user jobs. Many scientific applications comprise several tasks that are dependent in nature and are specified by workflow graphs. The aim of the cloud meta-scheduler is to schedule the user application tasks (and the applications) so as to optimize the resource utilization and to execute the user applications in minimum amount of time. During the past decade, there have been several attempts to use bio-inspired scheduling algorithms to obtain an optimal or near optimal schedule in order to minimize the overall schedule length and to optimize the use of resources. However, as the number of tasks increases, the solution space comprising different tasks-resource mapping sequences increases exponentially. Hence, there is a need to devise mechanisms to improvise the search strategies of the bio-inspired scheduling algorithms for better scheduling solutions in lesser number of iterations/time. The objective of the research work in this paper is to use bio-inspired bacteria foraging optimization algorithm (BFOA) along with other heuristics algorithms for better search of the scheduling solution space for multiple workflows. The idea is to first find a schedule by the heuristic algorithms such as MaxMin, MinMin, and Myopic, and use these as initial solutions (along with other randomly generated solutions) in the search space to get better solutions using BFOA. The performance of our approach with the existing approaches is compared for quality of the scheduling solutions. The results demonstrate that our hybrid approach (MinMin/Myopic with BFOA) outperforms other approaches.

Optimal broadcast scheduling method for VANETs: An adaptive discrete firefly approach

2020 ◽  
Vol 39 (6) ◽  
pp. 8125-8137
Author(s):  
Jackson J Christy ◽  
D Rekha ◽  
V Vijayakumar ◽  
Glaucio H.S. Carvalho
Keyword(s):  
Intelligent Transportation System ◽  
Search Algorithm ◽  
Mac Protocol ◽  
High Mobility ◽  
Optimal Solution ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Traffic Density ◽  
Scheduling Problem ◽  
Broadcast Scheduling

Vehicular Adhoc Networks (VANET) are thought-about as a mainstay in Intelligent Transportation System (ITS). For an efficient vehicular Adhoc network, broadcasting i.e. sharing a safety related message across all vehicles and infrastructure throughout the network is pivotal. Hence an efficient TDMA based MAC protocol for VANETs would serve the purpose of broadcast scheduling. At the same time, high mobility, influential traffic density, and an altering network topology makes it strenuous to form an efficient broadcast schedule. In this paper an evolutionary approach has been chosen to solve the broadcast scheduling problem in VANETs. The paper focusses on identifying an optimal solution with minimal TDMA frames and increased transmissions. These two parameters are the converging factor for the evolutionary algorithms employed. The proposed approach uses an Adaptive Discrete Firefly Algorithm (ADFA) for solving the Broadcast Scheduling Problem (BSP). The results are compared with traditional evolutionary approaches such as Genetic Algorithm and Cuckoo search algorithm. A mathematical analysis to find the probability of achieving a time slot is done using Markov Chain analysis.

scholarly journals A Novel Anomaly Behavior Detection Scheme for Mobile Ad Hoc Networks

Electronics ◽  
2021 ◽  
Vol 10 (14) ◽  
pp. 1635
Author(s):  
Neeraj Chugh ◽  
Geetam Singh Tomar ◽  
Robin Singh Bhadoria ◽  
Neetesh Saxena
Keyword(s):  
Anomaly Detection ◽  
Ad Hoc Networks ◽  
Mobile Ad Hoc Networks ◽  
Network Performance ◽  
Ad Hoc ◽  
Abnormal Behavior ◽  
Energy Awareness ◽  
Behavior Detection ◽  
Mobile Ad Hoc ◽  
Hoc Networks

To sustain the security services in a Mobile Ad Hoc Networks (MANET), applications in terms of confidentially, authentication, integrity, authorization, key management, and abnormal behavior detection/anomaly detection are significant. The implementation of a sophisticated security mechanism requires a large number of network resources that degrade network performance. In addition, routing protocols designed for MANETs should be energy efficient in order to maximize network performance. In line with this view, this work proposes a new hybrid method called the data-driven zone-based routing protocol (DD-ZRP) for resource-constrained MANETs that incorporate anomaly detection schemes for security and energy awareness using Network Simulator 3. Most of the existing schemes use constant threshold values, which leads to false positive issues in the network. DD-ZRP uses a dynamic threshold to detect anomalies in MANETs. The simulation results show an improved detection ratio and performance for DD-ZRP over existing schemes; the method is substantially better than the prevailing protocols with respect to anomaly detection for security enhancement, energy efficiency, and optimization of available resources.

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