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"The low-cost Wireless Sensor Network (WSN) consists of small battery powered devices called sensors, with limited energy capacity. Once deployed, accessibility to any sensor node for maintenance and battery replacement is not feasible due to the spatial scattering of the nodes. This will lead to an unreliable, limited lifetime and a poor connectivity network. In this paper a novel bio-inspired cluster-based deployment algorithm is proposed for energy optimization of the WSN and ultimately to improve the network lifetime. In the cluster initialization phase, a single cluster is formed with a single cluster head at the center of the sensing terrain. The second phase is for optimum cluster formation surrounding the inner cluster, based on swarming bees and a piping technique. Each cluster member distributes its data to its corresponding cluster head and the cluster head communicates with the base station, which reduces the communication distance of each node. The simulation results show that, when compared with other clustering algorithms, the proposed algorithm can significantly reduce the number of clusters by 38% and improve the network lifetime by a factor of 1/4."

"Wireless Sensor Network (WSN) technology has gained importance in recent years due to its various benefits, practicability and extensive utilization in diverse applications. The innovation helps to make real-time automation, monitoring, detecting and tracking much easier and more effective than previous technologies. However, as well as their benefits and enormous potential, WSNs are vulnerable to cyber-attacks. This paper is a systematic literature review of the security-related threats and vulnerabilities in WSNs. We review the safety of and threats to each WSN communication layer and then highlight the importance of trust and reputation, and the features related to these, to address the safety vulnerabilities. Finally, we highlight the open research areas which need to be addressed in WSNs to increase their flexibility against security threats."

"The demand for a Wireless Sensor Network (WSN) has increased enormously because of its great ability to supervise the outside world as well as due to its vast range of applications. Since these sensor nodes depend greatly on battery power and being deployed in adverse environments, substituting the battery is a tiresome job. Cluster-based routing techniques are prominent methods to extend the lifetime of wireless sensor networks. In this research, the work on energy efficient clustering approach is considered in two phases. During the cluster head selection phase, cluster heads are chosen which can stabilize the power consumption in sensor networks, by considering both the residual energy and distance of node with respect to sink. Later, during the cluster formation phase, a non-cluster head node will choose a cluster head that lies in close proximity with the center point between the sensor nodes and sink. Also, these non-cluster head nodes should be within the transmission range of the cluster head, as selected by the above method. Initially, the Low Energy Adaptive Clustering Hierarchy (LEACH) which is an eminent protocol for sensor networks is investigated. Furthermore, the same LEACH protocol is enhanced by proposing an effective cluster head election scheme as well as a new cluster formation scheme as mentioned above. Simulation results reveal that the proposed algorithm outperforms the traditional LEACH protocol in prolonging network lifetime."

"The low-cost Wireless Sensor Network (WSN) consists of small battery powered devices called sensors, with limited energy capacity. Once deployed, accessibility to any sensor node for maintenance and battery replacement is not feasible due to the spatial scattering of the nodes. This will lead to an unreliable, limited lifetime and a poor connectivity network. In this paper a novel bio-inspired cluster-based deployment algorithm is proposed for energy optimization of the WSN and ultimately to improve the network lifetime. In the cluster initialization phase, a single cluster is formed with a single cluster head at the center of the sensing terrain. The second phase is for optimum cluster formation surrounding the inner cluster, based on swarming bees and a piping technique. Each cluster member distributes its data to its corresponding cluster head and the cluster head communicates with the base station, which reduces the communication distance of each node. The simulation results show that, when compared with other clustering algorithms, the proposed algorithm can significantly reduce the number of clusters by 38% and improve the network lifetime by a factor of 1/4."

"Wireless Sensor Networks (WSNs) terdiri dari sejumlah besar sensor nodes, dan digunakan untuk berbagai aplikasi seperti pemantauan gedung, pengendalian lingkungan, pemantauan kehidupan habitat liar, deteksi kebakaran hutan, otomatisasi industri, militer, keamanan, dan kesehatan. Setiap sensor node memerlukan sistem operasi (SO) yang dapat mengontrol hardware, menyediakan abstraksi hardware untuk aplikasi perangkat lunak, dan mengisi kesenjangan antara aplikasi dan hardware. Dalam penelitian ini, peneliti menyajikan SO untuk WSNs dan percobaan dari portcontikiOS untuk MSP430 mikrokontroler yang sangat populer di platform hardware untuk WSNs. Peneliti memulai dengan menghadirkan isu utama yaitu desain SO untuk WSNs. Lalu, peneliti memeriksa beberapa sistem operasi populer untuk WSNs, termasuk TinyOS, ContikiOS, dan LiteOS. Akhirnya peneliti menyajikan sebuah percobaan dari port ContikiOS untuk MSP430 mikrokontroler.

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AbstractWireless Sensor Networks (WSNs) consist of a large number of sensor nodes, and are used for various applications such as building monitoring, environment control, wild-life habitat monitoring, forest fire detection, industry automation, military, security, and health-care. Each sensor node needs an operating system (OS) that can control the hardware, provide hardware abstraction to application software, and fill in the gap between applications and the underlying hardware. In this paper, researchers present OS for WSNs and an experiment of porting contikiOS to MSP430 microcontroller which is very popular in many hardware platforms for WSNs. Researchers begin by presenting the major issues for the design of OS for WSNs. Then, researchers examine some popular operating systems for WSNs including TinyOS, ContikiOS, and LiteOS. Finally, researchers present an experiment of porting ContikiOS to MSP430 microcontroller."

"Covers the low-power Wireless sensor network (WSN) services ranging from hardware platforms and communication protocols to network deployment, and sensor data collection and actuation. This book explains the implications of resource constraints and expected performance in terms of throughput, reliability and latency. "

"This book constitutes the refereed proceedings of the 9th European Conference on Wireless Sensor Networks, EWSN 2012, held in Trento, Italy, in Februar 2012. The 16 revised full papers presented were carefully reviewed and selected from 78 submissions. The papers are organized in topical sections on communication and security, system issues, reliability, localization and smart cameras, and hardware and sensing."

"ABSTRAKTesis ini adalah analisa konsumsi energi jaringan sensor nirkabel pada metode penyebaran yang berbeda dan protokol routing yang berbeda. Jaringan Sensor Nirkabel (JSN) muncul dengan banyak aplikasi, karena kemajuan komunikasi nirkabel dalam skala besar. Jaringan ini digunakan untuk melayani aplikasi objek tunggal, dengan persyaratan optimasi tinggi seperti penghematan daya. Masalah desain JSN adalah kompleksitas tinggi, dan membutuhkan metodologi yang kuat, termasuk dukungan simulasi. Pada tesis ini menggunakan NS2 sebagai program simulasi untuk model pengujian konsumsi energi. Pada tesis ini dibandingkan konsumsi energi pada tiga metode penyebaran yang berbeda dari JSN. Metode penyebaran ini mengacu pada topologi penyebaran. Dalam simulasi ini, disebarkan JSN dengan topologi grid, array, dan Random. Simulasi ini menggunakan jumlah node yang berbeda dari JSN untuk menunjukkan skalabilitasnya. Serta menggunakan AODV dan DSR sebagai protokol routing dan CBR sebagai lalu-lintas paket data. Setelah itu, membandingkan konsumsi energi yang dikonsumsi oleh jaringan tersebut. Berdasarkan hasil simulasi, topologi penyebaran random dengan protokol routing DSR adalah topologi terendah dengan konsumsi energinya 7.02% dibanding grid-DSR 7,34% dan array-DSR 7,99%, array-AODV 18,64% dibanding grid-AODV 27,30% dan random-AODV 31,71%. Kombinasi topologi penyebaran random dengan protokol routing DSR konsumsi energinya paling sedikit.

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ABSTRACTThis thesis is analysis of energy consumption the wireless sensor network at different deployment methods and different routing protocol. Wireless Sensor Networks (WSN) is emerging with many applications, because of the advances in large scale wireless communications. These networks are deployed to serve single objective application, with high optimization requirements such as power saving. The WSN design problem is of high complexity, and requires robust methodologies, including simulation support. This tesis uses NS2 as simulation program for the energy consumption testing model. In this tesis compare the energy consumption on three different deployment methods of WSN. These deployment methods refer to topology deployment. In this simulation, deployed WSN on grid, array, and random topology. This simulation uses a different numbers of WSN nodes for showing the scalability. And using AODV and DSR as routing protocol and CBR as the data packet traffic. After that, compare the energy consumption that consume by that network. Based on simulation result, the random deployment topology with DSR routing protocol is the topology of the lowest energy consumption of 7.02% than grid-DSR 7.34% and array-DSR 7.99%; array-AODV 18.64%, grid-AODV 27.30% and random-AODV 31.71%. The combination of random deployment topology with DSR routing protocol energy consumption at least."

"Efisiensi energi dan stream data mining pada Wireless Sensor Networks (WSN) adalah masalah yang sangat menarik untuk dibahas. Teknologi Routing Protocol dan Resource-Aware dapat dilakukan untuk meningkatkan efisiensi energi. Dalam penelitian ini peneliti mencoba untuk menggabungkan teknologi Routing Protocol menggunakan routing Distance Vector dan Resource-Aware (RA) framework pada Wireless Sensor Networks heterogen dengan menggabungkan sun-SPOT dan platform Imote2 Wireless Sensor Networks. RA melakukan proses pemantauan sumber daya dari memori, baterai, dan beban CPU lebih optimal dan efisien. Proses ini menggunakan Light-Weight Clustering (LWC) dan Light Weight Frequent Item (LWF). Hasil yang diperoleh bahwa dengan mengadaptasi Resource-Aware dalam Wireless Sensor Networks, masa pakai wireless sensor meningkatkan sampai ± 16,62%.

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AbstractEfficiency energy and stream data mining on Wireless Sensor Networks (WSNs) are a very interesting issue to be discussed. Routing protocols technology and resource-aware can be done to improve energy efficiency. In this paper we try to merge routing protocol technology using routing Distance Vector and Resource-Aware (RA) framework on heterogeneity wireless sensor networks by combining sun-SPOT and Imote2 platform wireless sensor networks. RA perform resource monitoring process of the battery, memory and CPU load more optimally and efficiently. The process uses Light-Weight Clustering (LWC) and Light Weight Frequent Item (LWF). The results obtained that by adapting Resource-Aware in wireless sensor networks, the lifetime of wireless sensor improve up to ± 16.62%."

"k Berbahasa Indonesia/Berbahasa Lain (Selain Bahasa Inggris): Wireless Sensor Networks (WSN) terdiri dari node sensor yang tersebar dalam area monitoring untuk mengumpulkan dan mengirimkan data. Namun, keterbatasan energi pada node sensor menjadi tantangan utama dalam memperpanjang network lifetime. Ketergantungan pada baterai sebagai sumber daya menyebabkan node sensor mudah mengalami kehabisan energi, yang pada akhirnya memengaruhi kinerja jaringan. Oleh karena itu, diperlukan pendekatan yang efektif untuk mengurangi konsumsi energi dan menyeimbangkan distribusi beban dalam jaringan sensor. Penelitian ini mengusulkan protokol Single-Hop Clustering Routing berbasis Tuna Swarm Optimization (TSO) dan Gravitational Search Algorithm (GSA). Algoritma TSO digunakan untuk membentuk cluster secara optimal dengan meminimalkan jarak komunikasi antar node dalam cluster, sedangkan GSA diterapkan untuk memilih cluster head (CH) berdasarkan faktor-faktor seperti residual energy, jarak ke base station (BS), dan jarak intracluster. Hasil simulasi menunjukkan bahwa algoritma TSO-GSA mampu meningkatkan efisiensi energi dan memperpanjang lifetime jaringan secara signifikan dibandingkan protokol referensi TSO-FC. Pada skenario utama dengan 100 node dalam area 150 × 150 m², TSO-GSA mencatat peningkatan lifetime jaringan sebesar 24.03% pada LND (1615 round dibandingkan 1302 round oleh TSO-FC). Namun, sebagai trade-off, FND pada TSO-GSA terjadi lebih awal, yaitu pada round ke-444 dibandingkan round ke-902 pada TSO-FC. Di sisi lain, protokol ini mampu mempertahankan energi residu yang lebih tinggi, mencapai peningkatan sebesar 17,22% pada round ke-800 dibandingkan TSO-FC. Selain itu, algoritma TSO-GSA menunjukkan adaptabilitas yang baik terhadap perubahan kompleksitas jaringan, dengan peningkatan LND sebesar 26,7% dalam lingkungan dengan 200 node. Dalam hal performa komunikasi, protokol ini juga meningkatkan jumlah total data yang diterima BS sebesar 12,5% dibandingkan TSO-FC. Dengan keunggulan-keunggulan tersebut, penelitian ini menyimpulkan bahwa protokol TSO-GSA dapat menjadi solusi efektif untuk mengoptimalkan efisiensi energi dan memperpanjang lifetime jaringan dalam WSN.

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Wireless Sensor Networks (WSN) consist of sensor nodes distributed in a monitoring area to collect and transmit data. However, the limited energy of sensor nodes is a major challenge in extending network lifetime. Dependence on batteries as a power source causes sensor nodes to easily run out of energy, which ultimately affects network performance. Therefore, an effective approach is needed to reduce energy consumption and balance load distribution in sensor networks. This research proposes a Single-Hop Clustering Routing protocol based on Tuna Swarm Optimization (TSO) and Gravitational Search Algorithm (GSA). The TSO algorithm is used to form clusters optimally by minimizing the communication distance between nodes in the cluster, while GSA is applied to select the cluster head (CH) based on factors such as residual energy, distance to the base station (BS), and intracluster distance. Simulation results show that the TSO-GSA algorithm is able to significantly improve energy efficiency and extend network lifetime compared to the reference protocol TSO-FC. In the main scenario with 100 nodes in a 150 × 150 m² area, TSO-GSA recorded a 24.03% increase in network lifetime on LND (1615 rounds compared to 1302 rounds by TSO-FC). However, as a trade-off, FND in TSO-GSA occurs earlier, at 444th round compared to 902nd round in TSO-FC. On the other hand, this protocol is able to maintain higher residual energy, achieving an improvement of 17.22% in the 800th round compared to TSO-FC. Moreover, the TSO-GSA algorithm shows good adaptability to changes in network complexity, with a 26.7% improvement in LND in a 200-node environment. In terms of communication performance, the protocol also increases the total amount of data received by the BS by 12.5% compared to TSO-FC. With these advantages, this study concludes that the TSO-GSA protocol can be an effective solution to optimize energy efficiency and extend network lifetime in WSNs. "