Scheduled activity energy-aware distributed cluster- based routing algorithm for wireless sensor networks with non-uniform node distribution

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(1)UNIVERSITI PUTRA MALAYSIA SCHEDULED ACTIVITY ENERGY-AWARE DISTRIBUTED CLUSTERBASED ROUTING ALGORITHM FOR WIRELESS SENSOR NETWORKS WITH NON-UNIFORM NODE DISTRIBUTION. NOOSHIN NOKHANJI. FSKTM 2014 22.

(2) PM. H. T. U. SCHEDULED ACTIVITY ENERGY-AWARE DISTRIBUTED CLUSTERBASED ROUTING ALGORITHM FOR WIRELESS SENSOR NETWORKS WITH NON-UNIFORM NODE DISTRIBUTION. IG. By. ©. C. O. PY. R. NOOSHIN NOKHANJI. Thesis Submitted to the School of Graduate Studies, Universiti Putra Malaysia, in Fulfilment of the Requirements for the Degree of Master of Science. September 2014.

(3) All material contained within the thesis, including without limitation text, logos, icons, photographs and all other artwork, is copyright material of Universiti Putra Malaysia unless otherwise stated. Use may be made of any material contained within the thesis for non-commercial purposes from the copyright holder. Commercial use of material may only be made with the express, prior, written permission of Universiti Putra Malaysia.. ©. C. O. PY. R. IG. H. T. U. PM. Copyright © Universiti Putra Malaysia.

(4) Abstract of thesis presented to the Senate of Universiti Putra Malaysia in fulfilment of the requirement for the degree of Master of Science. By. H. Chair: Zurina Mohd Hanapi, PhD. T. September 2014. U. NOOSHIN NOKHANJI. PM. SCHEDULED ACTIVITY ENERGY-AWARE DISTRIBUTED CLUSTERBASED ROUTING ALGORITHM FOR WIRELESS SENSOR NETWORKS WITH NON-UNIFORM NODE DISTRIBUTION. IG. Faculty: Computer Science and Information Technology. ©. C. O. PY. R. The main and definitive target of routing protocols in Wireless Sensor Networks (WSN) is passing data from the sensor nodes to the sink in most energy efficient manner besides considering the accuracy of data. Among different categories of routing protocols based on the network architecture, cluster-based (hierarchical) routing protocols are more energy efficient and increase the scalability as well as lifetime of the network. The non-uniform node deployment makes the energy consumption of the nodes more imbalanced. It makes the cluster-based routing protocols less efficient. Energy Aware Distributed Clustering (EADC) is one of the cluster-based routing protocol proposed for networks with non-uniform node distribution, which can effectively balance the energy consumption among the nodes. However, since the density of nodes varies in each region due to the non-uniform node deployment, in the dense area the sensed and transmitted data are extremely co-related and redundant. Therefore, the sensor nodes consume more inessential energy. Nevertheless, this unnecessary energy consumption is not considered in the EADC. Therefore, in this study, a new algorithm called Scheduled-Activity Energy Aware Distributed Clustering (SA-EADC) is proposed. SA-EADC adds another phase as “sensor redundancy check and activation” to EADC. It identifies the redundant sensor nodes, whose sensing coverage area are also covered completely by their direct neighbors and turns off them. In order to schedule the activity of these sensor nodes and to avoid creation of coverage holes, a distributed self-inactivation approach is proposed, in which the redundant sensor nodes work alternatively based on their residual energy. The proposed algorithm maintains the original sensing coverage, and guarantees sensing reliability. The results shows that SA-EADC algorithm can effectively identify the redundant nodes and schedule them to activate alternatively in i.

(5) ©. C. O. PY. R. IG. H. T. U. PM. a way that it reduces the overall system energy consumption and extends the network lifetime without degradation in coverage and sensing reliability of the network.. ii.

(6) Abstrak tesis yang dikemukakan kepada Senat Universiti Putra Malaysia sebagai memenuhi keperluan untuk ijazah Sarjana Sains. Oleh. T. September 2014. U. NOOSHIN NOKHANJI. PM. AKTIVITI BERJADUAL TENAGA SEDAR ALGORITMA PENGHALAAN BERASASKAN KELOMPOK TERAGIH UNTUK RANGKAIAN SENSOR WAYARLES DENGAN PENGAGIHAN NOD TIDAK SERAGAM. H. Pengerusi: Zurina Mohd Hanapi, PhD. IG. Fakulti: Sains Komputer dan Teknologi Maklumat. ©. C. O. PY. R. Sasaran utama dan muktamad protokol penghalaan dalam rangkaian sensor wayarles (WSN) adalah menghantar data daripada nod sensor kepada lubuk data dengan tenaga yang cekap di samping memastikan ketepatan data. Diantara kategori protokol penghalaan yang berdasarkan seni bina rangkaian, protokol penghalaan berasaskan kelompok (hierarki) mempunyai tenaga yang efisen dan berkebolehan meningkatkan boleh skala dan juga hayat rangkaian. Namun, pelaksanaan nod tidak seragam menyebabkan penggunaan tenaga nod yang tidak seimbang. Ia menjadikan protokol penghalaan berasaskan kelompok menjadi kurang cekap. Kelompok Tenaga Sedar Teragih (EADC) adalah salah satu protokol penghalaan berasaskan kelompok yang dicadangkan untuk sesebuah rangkaian dengan pengagihan nod yang tidak seragam, yang berkesan dalam mengimbangi penggunaan tenaga antara nod dengan lebih berkesan. Walau bagaimanapun, disebabkan ketumpatan nod adalah berbeza bagi setiap kawasan kerana penggunaan nod yang tidak seragam, di kawasan yang padat, pengesanan dan penghantaran data mempunyai hubung kait yang rapat dan bertindan. Oleh itu, nod sensor menggunakan banyak tenaga yang tidak perlu. Namun, penggunaan tenaga yang tidak perlu ini tidak diambilkira dalam EADC. Oleh itu, dalam kajian ini, algoritma baru yang dipanggil Aktiviti Berjadual Tenaga Sedar Kelompok Teragih (SA-EADC) telah dicadangkan. SA-EADC menambah fasa lain iaitu "sensor pemeriksaan lebihan dan pengaktifan" untuk EADC. Ia mengenal pasti nod sensor yang bertindan, dimana penderiaan kawasan liputan juga dideria sepenuhnya oleh jiran-jiran secara terus dan dimatikan mereka. Untuk menjadualkan aktiviti nod sensor ini dan mengelakkan pembentukan lubang liputan, pendekatan pengaktifan secara bersendirian yang teragih adalah dicadangkan, di mana nod sensor yang bertindan bekerja secara alternatif berasaskan tenaga sisa mereka. Algoritma yang dicadangkan ini mengekalkan liputan penderiaan asal dan menjamin iii.

(7) ©. C. O. PY. R. IG. H. T. U. PM. kebolehpercayaan penderiaan. Keputusan dalam penyelidikan ini menunjukkan bahawa algoritma SA-EADC berkesan dan boleh mengenal pasti nod bertindan dan menjadualkan pengaktifan alternatif dengan mengurangkan penggunaan keseluruhan sistem tenaga dan mampu memanjangkan jangka hayat rangkaian tanpa mengurangkan liputan dan kebolehpercayaan penderiaan rangkaian.. iv.

(8) ACKNOWLEDGEMENTS. PM. I would like to express my deepest appreciation and gratitude to the supervisory committee led by Dr. Zurina Mohd Hanapi and committee members Associate Prof. Dr. Shamala Subramaniam and Dr. Mohamad Afandee Mohemad for the various guidance, sharing of intellectual experiences and in giving me the vital help to conquer the numerous challenges of this study. I also want to extend my profound appreciation to my beloved family for their love, affection, and invaluable support over years. Thank you for the fully shore up, comfort, and encouragement, which bring this thesis to the end.. ©. C. O. PY. R. IG. H. T. U. Finally, I would like to convey my sincere thanks to my friends, who assist me whenever I faced the problems.. v.

(9) Hamidah bt Ibrahim, PhD Professor Faculty of Computer Science and Information Technology Universiti Putra Malaysia (Chairman). H. T. Mohamed b Othman, PhD Professor Faculty of Computer Science and Information Technology Universiti Putra Malaysia (Internal Examiner). U. Members of the Thesis Examination Committee were as follows:. PM. I certify that a Thesis Examination Committee has met on 8 September 2014 to conduct the final examination of Nooshin Nokhanji on her thesis entitled " Scheduled Activity Energy-Aware Distributed Cluster-Based Routing Algorithm for Wireless Sensor Networks with Non-Uniform Node Distribution" in accordance with the Universities and University Colleges Act 1971 and the Constitution of the Universiti Putra Malaysia [P.U.(A) 106] 15 March 1998. The Committee recommends that the student be awarded the Master of Science.. ©. C. O. PY. Norashidah Md Din, PhD Professor College of Engineering Universiti Tenaga Nasional Malaysia (External Examiner). R. IG. Zuriati bt Ahmad Zukarnain, PhD Associate Professor Faculty of Computer Science and Information Technology Universiti Putra Malaysia (Internal Examiner). ZULKARNAIN ZAINAL, PhD Professor and Deputy Dean School of Graduate Studies Universiti Putra Malaysia. Date: 23 January 2015. vi.

(10) Zurina Mohd Hanapi, PhD Senior Lecturer Faculty of Computer Science and Information Technology Universiti Putra Malaysia (Chairman). H. T. U. Shamala Subramaniam, PhD Associate Professor Faculty of Computer Science and Information Technology Universiti Putra Malaysia (Member). PM. This thesis was submitted to the Senate of Universiti Putra Malaysia and has been accepted as fulfilment of the requirement for the degree of Master of Science. The members of the Supervisory Committee were as follows.. ©. C. O. PY. R. IG. Mohamad Afendee Mohamed, PhD Senior Lecturer Faculty of Computer Science and Information Technology Universiti Putra Malaysia (Member). BUJANG BIN KIM HUAT, PhD Professor and Dean School of Graduate Studies Universiti Putra Malaysia. Date:. vii.

(11) Declaration by graduate student. Date: 2 March 2015. IG. Signature: _______________________. H. T. U. PM. I hereby confirm that:  this thesis is my original work;  quotations, illustrations and citations have been duly referenced;  this thesis has not been submitted previously or concurrently for any other degree at any other institutions;  intellectual property from the thesis and copyright of thesis are fully-owned by Universiti Putra Malaysia, as according to the Universiti Putra Malaysia (Research) Rules 2012;  written permission must be obtained from supervisor and the office of Deputy Vice-Chancellor (Research and Innovation) before thesis is published (in the form of written, printed or in electronic form) including books, journals, modules, proceedings, popular writings, seminar papers, manuscripts, posters, reports, lecture notes, learning modules or any other materials as stated in the Universiti Putra Malaysia (Research) Rules 2012;  there is no plagiarism or data falsification/fabrication in the thesis, and scholarly integrity is upheld as according to the Universiti Putra Malaysia (Graduate Studies) Rules 2003 (Revision 2012-2013) and the Universiti Putra Malaysia (Research) Rules 2012. The thesis has undergone plagiarism detection software.. ©. C. O. PY. R. Name and Matric No.: Nooshin Nokhanji (GS32968). viii.

(12) Declaration by Members of Supervisory Committee This is to confirm that:  the research conducted and the writing of this thesis was under our supervision;  supervision responsibilities as stated in the Universiti Putra Malaysia (Graduate Studies) Rules 2003 (Revision 2012-2013) are adhered to.. ©. C. O. PY. R. U. IG. H. Signature: Name of Member of Supervisory Committee: Shamala Subramaniam, PhD. PM. Signature: Name of Member of Supervisory Committee: Mohamad Afendee Mohammed, PhD. T. Signature: Name of Chairman of Supervisory Committee: Zurina Mohd. Hanapi, PhD. ix.

(13) TABLE OF CONTENTS Page i. ABSTRAK. iii. ACKNOWLEDGEMENTS. v. APPROVAL. vi. PM. ABSTRACT. DECLARATION. viii. LIST OF TABLES. xiii. LIST OF FIGURES. xiv xvi. U. LIST OF ABBREVIATIONS CHAPTER INTRODUCTION. T. 1. H. 1.1 Background 1.2 Problem Statement 1.4 Research Scope. 2 2 2. 1.6 Thesis Organization. 3. LITERATURE REVIEW. 4. 2.1 Introduction. 4. 2.2 Wireless Sensor Networks. 4. R. 3. C. O. 2.2.1 Architecture of WSN. ©. 1. 1.5 Research Contribution. PY. 2. IG. 1.3 Research Objective. 1. 4. 2.2.2 Sensor Node Architecture. 5. 2.2.3 Application of WSN. 6. 2.2.4 Design Issues and Challenges in WSN. 8. 2.2.5 Energy Efficiency Research Issues in WSN. 9. 2.3 Routing Protocols and Design Challenges. 9. 2.4 Classification of Routing Protocols in WSN. 12. 2.5 Cluster-Based Routing Protocols. 13. 2.5.1 General Phases of Clustering. 14. 2.5.2 Prominent Energy Efficient Cluster-Based Routing Protocols. 15. x.

(14) 2.5.3 Comparison of Prominent Cluster-Based Routing Protocols in WSN 2.6 Sensor Activity Scheduling. 31. 2.6.2 Activity Scheduling Procedures. 34. PM. 34. METHODOLOGY. 36. 3.1 Introduction. 36. 3.2 Research Framework. 36. U. 3.2.1 Research Problem. 3.2.3 Conducting Simulation Experiments. 42. 3.2.4 Performance Metrics Evaluation and Comparison. 42. H. T. 36. IG. 3.3.1 Computer Resources. 43. 3.3.3 Simulation Parameters. 44. 3.3.4 Performance Metrics. 44. 3.3.5 Simulation Assumptions. 45. R. 43. PY. 45. 3.4.1 Cluster Head Distribution. 46. 3.4.2 Network Lifetime. 48 49. O. 3.5 Summary. C. 43. 3.3.2 Network Topologies. 3.4 Simulation Validation. ©. 36. 3.2.2 Scheduled Activity Energy Aware Distributed Clustering Algorithm. 3.3 Simulation Environment. 4. 31. 2.6.1 Redundancy Check Methods 2.7 Summary 3. 27. SCHEDULED ACTIVITY ENERGY AWARE DISTRIBUTED CLUSTERING. 50. 4.1 Introduction. 50. 4.2 SA-EADC Model. 50. 4.3 SA-EADC Algorithm. 52. 4.4 Performance Evaluation. 54. 4.5 Theoretical Analysis. 54. 4.5.1 Control Message Complexity. 54. 4.5.2 Time Complexity. 55. 4.6 Simulation Analysis. 56 xi.

(15) 56. 4.6.2 Energy Consumption Evaluation. 60. 4.7 Summary. 64. CONCLUSION AND FUTURE WORKS. 65. 5.1 Conclusion. 65. 5.2 Future Works. 66. PM. 5. 4.6.1 Coverage Preservation Evaluation. REFERENCES. 67 73. U. BIODATA OF STUDENT. 74. ©. C. O. PY. R. IG. H. T. LIST OF PUBLICATIONS. xii.

(16) LIST OF TABLES. Table. 3.1. Comparison of Energy Efficient Cluster-Based Routing Protocols in WSN Comparison of Energy Efficient Cluster-Based Routing Protocols in WSN (Continue) Description of Control Messages and States in SA-EADC. 3.2. Simulation Parameters. 4.1. Control Messages and Time Complexity Comparison. 30 38 44. ©. C. O. PY. R. IG. H. T. U. 2.2. 29. PM. 2.1. Page. xiii. 56.

(17) LIST OF FIGURES. Figure. Page Architecture of WSN. 5. 2.2. Sensor Node Architecture. 6. 2.3. Different Classifications of Routing Protocol. 2.4. General Phases of Clustering in One Round. 2.5. Topology of LEACH. 2.6. Topology of PEGASIS. 2.7. Topology of FZ-LEACH. 2.8. Topology of ACT. 2.9. Topology of CCM. 2.10. Sponsored Sector Redundancy Check Method. 2.11. Perimeter Coverage Redundancy Check Method. 33. 2.12. Crossing Coverage Redundancy Check Method. 33. 3.1. Research Framework. 37. 3.2. Pseudo Code of Information Collection Phase. 39. 3.3. Pseudo Code of Cluster Head Competition Phase. 40. 3.4. Pseudo Code of Cluster Formation Phase. 40. PM. 2.1. 12 14. U. 16 18. O. PY. R. IG. H. T. 22 23 24 32. Pseudo Code of Cluster-Based Routing Algorithm. 42. 3.6. Network Topology in Two Scenarios. 43. 3.7. Number of Cluster Head Generated in Scenario 1 Implemented in NS2 and Clustering Algorithm Simulator. 46. Number of Cluster Head Generated in Scenario 2 Implemented in NS2 and Clustering Algorithm Simulator. 46. Distribution of the Number of CHs in Scenario 1 Implemented in NS2 and Clustering Algorithm Simulator. 47. Distribution of the Number of CHs in Scenario 2 Implemented in NS2 and Clustering Algorithm Simulator. 47. ©. C. 3.5. 3.8 3.9. 3.10. xiv.

(18) Network Lifetime in Scenario 1 Implemented in NS2 and Clustering Algorithm Simulator. 48. 3.12. Network Lifetime in Scenario 2 Implemented in NS2 and Clustering Algorithm Simulator. 48. 4.1. SA-EADC Model. 51. 4.2. Pseudo Code of Sensor Redundancy Check and Activity Scheduling Phase. 54. PM. 3.11. 4.3. Network Sensing Coverage in Scenario 1. 57. 4.4. Network Sensing Coverage in Scenario 2. 4.5. Different Sensing Degree of Network in Scenario 1. 4.6. Different Sensing Degree of Network in Scenario 2. 59. 4.7. Number of Active Nodes in Each scenario. 60. 4.8. Number of Inactive Nodes vs. Node Density. 4.9. Network Lifetime of Scenario 1. 61. 4.10. Network Lifetime of Scenario 2. 62. 4.11. Average Energy Dissipation per Round in Scenario 1. 63. 4.12. Average Energy Dissipation per Round in Scenario 2. 63. ©. C. O. PY. R. IG. H. T. U. 57. xv. 58. 60.

(19) Algorithm for Cluster Establishment. ACT. Arranging Cluster Size and Transmission ranges. ADC. Analog-to-Digital Convertor. AMRP. Average Minimum Reachability Power. BCDCP. Base station Controlled Dynamic Clustering Protocol. BS. Base Station. CBC. Centralized Balanced Clustering Routing Protocol. CCM. Chain Cluster-based Mixed. CDMA. Code Division Multiple Access. CH. Cluster Head. CM. Cluster Member. DD. Directed Diffusion. DES. Discrete Event Simulation. DIST-TH. Distance Threshold. EADC. Energy-Aware Distributed Clustering Energy Aware Distributed Unequal Clustering Energy Aware Routing. O. EAR. PY. EADUC. R. IG. H. T. U. ACE. Energy Efficient Clustering Scheme. EEHC. Energy Efficient Heterogeneous Clustered. EEUC. Energy Efficient Unequal Clustering. FS. Free Space. FZ-LEACH. Far Zone- Low Energy Adaptive Clustering Hierarchy. GAF. Geographic Adaptive Fidelity. GEAR. Geographic and Energy Aware Routing. GOAFR. Greedy Other Adaptive Face Routing. ©. C. EECS. xvi. PM. LIST OF ABBREVIATIONS.

(20) Global Positioning System. HEED. Hybrid Energy-Efficient Distributed Clustering. ID. Identity. LEACH. Low Energy Adaptive Clustering Hierarchy. LEACH-C. Low Energy Adaptive Clustering Hierarchy Centralized. MAC. Medium Access Control. MEMS. Micro-Electro-Mechanical Systems. MECN. Minimum Energy Communication Network. MP. Multipath. MR-LEACH. Multi hop Routing with LEACH. MRP. Minimum Reachability Power. MSE. Mobile Sink-Based Improved Algorithm for Stable Election. MST. Minimum Spanning Tree. PEGASIS. Power-efficient Gathering in Sensor Information Systems. QoS. Quality of Service. RF. Radio Frequency. PY. R. IG. H. T. U. PM. GPS. Scheduled-Activity Energy-Aware Distributed Clustering. SAR. Sequential Assignment Routing. SMECN. Small Minimum-Energy Communication Network. O. SA-EADC. Sensor Protocols for Information via Negotiation. TDMA. Time Division Multiple Access. UCS. Unequal Clustering Size. WSN. Wireless Sensor Networks. ZH. Zone Head. ©. C. SPIN. xvii.

(21) CHAPTER 1 INTRODUCTION. 1.1 Background. T. U. PM. The combination of innovations in Micro-Electro-Mechanical Systems (MEMS) and the development of low power radio technologies, in addition to the advances in low-power embedded micro-controllers, result in appearing a special type of ad-hoc networks called Wireless Sensor Networks (WSN) (Younis & Fahmy, 2004; Lindsey, Raghavendra, & Sivalingam, 2002; Heinzelman, Chandrakasan, & Balakrishnan, 2000). WSNs have achieved a significant amount of attention in recent years, because of their benefits in sensing and gathering different kinds of data from various environments. WSNs consist of hundred to thousand sensor nodes, which measure a property from the environment as well as processing and transmitting the collected data to the Base Station (BS) (Yick, Mukherjee, & Ghosal, 2008).. R. IG. H. There are many factors, which influence the design of a sensor network, such as fault tolerance, scalability, resources constraints, power consumption, transmission media, and security. In many applications, battery replacement or node redeployment is impossible. Therefore, the network strongly depends on the battery lifetime of sensor nodes. The malfunction of nodes may cause significant topology changes, rerouting of packets and network reorganization (Akyildiz, Su, Sankarasubramaniam, & Cayirci, 2002). Thus, energy efficiency is a very critical issue, which notably affects the network lifetime. Hence, the main concern in designing protocols is how to minimize the energy consumption and maximize the network lifetime (Gu, Yu, Yu, Wang, & Lv, 2014).. O. PY. The problem of energy consumption can be discussed in two aspects; developing energy efficient communication protocols and identifying wasteful and unnecessary activities in the network and pacifying their impact (Dargie & Poellabauer, 2010). Routing protocols has a key role in WSNs, since it is the most energy-conserving factor. They are responsible for discovering and maintaining energy efficient route in the network, in order to make communication reliable and efficient (Roseline & Sumath, 2011; Al-Karaki & Kamal, 2004).. ©. C. Node deployment is one of the challenging factors in design of routing protocols. It has influence on energy consumption, coverage, lifetime, throughput of network. Node deployment can be manual, randomized, uniform, or non-uniform (Al-Karaki & Kamal, 2004). It has been proved by many researchers that among different categories of protocols based on the network architecture, cluster-based (hierarchical) routing protocols are more energy efficient than noncluster based routing protocols, since they increase the scalability and lifetime of the network (Liu, 2012; Naeimi, Ghafghazi, Chow, & Ishii, 2012; Yu, Qi, & Wang, 2011; Heinzelman et al., 2000). However, non-uniform node deployment makes the cluster-based routing protocols less efficient, since the energy consumption of the nodes are more imbalanced.. 1.

(22) The main motivation of this research work is to design a cluster- based routing algorithm for the network with non-uniform node distribution in order to extend the lifetime and decrease the energy consumption. 1.2 Problem Statement. U. PM. In the network with a non-uniform node deployment, the mechanisms used to balance the energy consumption and extend the network lifetime are not always effective. The non-uniform node deployment makes the energy consumption of the nodes more imbalanced (Yu, Qi, Wang, & Gu, 2012). It makes the cluster-based routing protocols less efficient (Yu et al., 2012; Shin, Moh, & Chung, 2011). Yu et al. (2012) proposed a cluster-based routing protocol for the network with non-uniform node distribution, which includes EADC, and a cluster-based routing algorithm. This routing protocol significantly balances the energy consumption among the nodes and prolongs the network lifetime.. 1.3 Research Objective. IG. H. T. However, as the density of the sensor nodes varies in each region due to the nonuniform node distribution, in the dense area the sensed and transmitted data are extremely correlated and redundant. Thus, the sensor nodes consume more inessential energy for sensing and transmitting redundant data. Nevertheless, this unnecessary energy consumption is not considered in EADC, which decreases the network lifetime.. PY. R. The aim of this research work is to propose a scheduled activity energy-aware distributed clustering algorithm, which identifies the redundant sensor nodes, and schedules their activity alternatively in order to reduce the energy consumption and increase the lifetime of the network with non-uniform node distribution. 1.4 Research Scope. ©. C. O. This research work focuses on the EADC routing protocol, since it balances the energy consumption among the nodes in the network with non-uniform node distribution and increases the network lifetime significantly. Furthermore, it is a distributed routing protocol, which takes the advantage of heterogeneous nodes in terms of energy. Therefore, the choice of the EADC protocol is considered as a good platform to fulfil the objectives. This study focuses on the lifetime and energy consumption improvements of the network, since they are the main concern in the design of the protocols for WSN. The study covers two main scenarios, in which the sensor nodes are distributed randomly (i.e. the location of the nodes is chosen randomly) and non-uniformly (i.e. the nodes are more grouped in certain parts of the network) in a square field, while the BS is located outside of the field. The location of the BS and the sensor nodes are fixed. The BS has sufficient energy resource and its location is known by each node. All the sensor nodes are heterogeneous in terms of energy and location unaware. They can use power control to vary the amount of transmit power. Additionally, they are 2.

(23) required to be time synchronized. The failure of the sensor nodes is due to the energy depletion. 1.5 Research Contribution. PM. In this research work, an energy aware distributed clustering algorithm for the network with non-uniform node distribution was proposed in order to solve the existing problem of EADC. The proposed algorithm improves the performance of EADC algorithm in terms of energy consumption and lifetime. The contribution of this study can be defined in details as follows:. IG. 1.6 Thesis Organization. H. T. U. A Scheduled-Activity Energy-Aware Distributed Clustering (SA-EADC) was proposed in order to solve the problem of inessential energy consumption of the network due to the redundancy of the nodes. SA-EADC exploits the redundant nodes and turns them off for the current round. The redundant nodes are scheduled based on their residual energy to work alternately. The proposed algorithm preserves the original sensing coverage, and guarantees a certain redundancy. Consequently, SAEADC avoids unnecessary redundant sensing and transmission of data, which results in reducing the overall energy consumption of the system and extending the network lifetime.. R. The thesis includes five chapters. Chapter 1 presents a brief discussion on the background, problem statement, objectives, scopes, and findings of the research work.. PY. Chapter 2 presents a literature study to review the main principles in WSN, energy efficiency issues, classifications of routing protocols in WSN, cluster-based routing protocols, deep analysis of prominent cluster-based routing protocols, and sensor activity scheduling.. C. O. Chapter 3 explains the general research methodology used to accomplish the objective. It presents the framework of the research work and explores each stage in details. It covers the aspects of design, algorithm implementation, simulation parameters, and performance metrics.. ©. Chapter 4 presents the proposed clustering algorithm SA-EADC in detail. The design of SA-EADC is described thoroughly and its performance is evaluated based on the simulation analysis in this chapter. Finally, this study is concluded and directions for future work are presented in chapter 5.. 3.

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