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"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 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."

"Wireless sensor network (WSN) adalah sekelompok node sensor yang mengambil data dengan parameter pengukuran tertentu dan kemudian mengirim data secara nirkabel ke node pusat atau server untuk pemrosesan data. Salah satu hal yang paling penting dalam WSN adalah umur dari jaringan. Node sensor dalam WSN dirancang agar memiliki bentuk yang kecil sehingga mudah untuk dipindahkan, diganti dan rendah biaya produksi. Untuk mendukung desain tersebut maka energi dari node sensor dalam WSN biasanya tergantung baterai yang terintegrasi. Sehingga umur dari WSN tergantung pada kapasitas baterai dari masing-masing node sensor. Node sensor harus bekerja seefisien mungkin agar penggunaan energi dapat lebih hemat sehingga umur WSN bisa lebih panjang. Semakin lama umur WSN, maka diharapkan semakin tinggi total data atau semakin banyak data yang dikirimkan. Pada proses transmisi data, node sensor mengkonsumsi lebih banyak energi daripada saat melakukan proses data; Oleh karena itu, WSN perlu menggunakan metode routing untuk menghemat energi pada saat proses transmisi. Salah satu dari banyak cara untuk memperpanjang umur WSN adalah dengan menggunakan konsep pengelompokan node atau disebut dengan metode klaster. Salah satu protokol routing yang menggunakan konsep klaster adalah LEACH. Penelitian ini mengusulkan metode routing DivNCGL yang dimodifikasi berdasarkan LEACH dengan cara mendistribusikan cluster heads (CHs) untuk mencegah terpilihnya CH yang berdekatan. Proses distribusi dilakukan dengan cara membagi luas area sebaran node diawal proses set-up menjadi subregion. Proses pembagian subregion menggunakan nilai probabilitas yang didapatkan dengan metode non-cooperative game berdasarkan sisa node aktif, nilai energi total yang tersisa, dan energi yang dibutuhkan untuk melakukan transmisi. Parameter evalusi dilihat dari umur jaringan, total disipasi energi dan total data terkirim. Perbandingan simulasi akan melihat dari 3 metode yaitu LEACH, LEACH dengan probabilitas non-cooperative game (NCGL), dan DivNCGL. Dari hasil simulasi, umur WSN menggunakan metode DivNCGL meningkat lebih dari 30% dengan disipasi energi yang stabil dibandingkan dengan protokol LEACH. Peningkatan umur WSN akan meningkatkan jumlah data yang dikirimkan dan data yang diterima dengan menggunakan metode DivNCGL meningkat mencapai 70% dibandingkan dengan LEACH.

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A wireless sensor network (WSN) is a group of sensor nodes that take data with specific measurement parameters and then send the data wirelessly to a central node or server for data processing. One of the most critical things in WSN is the age of the network. The sensor nodes in WSN are designed to be compact, so they are easy to move or replace, with low production costs. To support the compact design of sensor nodes, the energy from the sensor nodes in the WSN usually depends on the integrated battery. So the lifespan of the WSN depends on the battery capacity of each sensor node. The sensor node must work as efficiently as possible so that energy use can be more efficient so that the WSN life can be longer. The longer the lifespan of the WSN, it is expected for higher total data sent. In the data transmission process, the sensor node consumes more energy than when processing data; Therefore, WSN needs to use a routing method to save energy during the transmission process. One of the many ways to extend the life of the WSN is to use the concept of grouping nodes or the so-called cluster method. One of the routing protocols that use the cluster concept is LEACH. This study proposes the DivNCGL routing method, a modified method based on LEACH by distributing cluster heads (CHs) to prevent the selection of adjacent CH. The distribution process is carried out by dividing the distribution area of ​​the nodes at the beginning of the setup process into subregions. The subregion division process uses the probability value obtained by the non-cooperative game method based on the remaining active nodes, the total remaining energy, and the energy required for transmission. Parameter evaluation is seen from network lifetime, total energy dissipation, and total data sent. The simulation comparison will look at 3 methods, namely LEACH, LEACH with probability non-cooperative game (NCGL), and DivNCGL. From the simulation results, the lifespan of WSN using the DivNCGL method increased up to 30% with stable energy dissipation compared to the LEACH protocol. The increasing lifespan of the WSN also increases the amount of data transmitted. Using the DivNCGL method, the received data increased up to 70% compared to LEACH."

"WSN merupakan jaringan sensor berskala besar dengan sumber daya yang terbatas. WSN digunakan pada aplikasi yang bersifat spesifik seperti untuk militer, survei, industri sampai pada pemakaian umum. Masalah yang dihadapi WSN adalah keterbatasan sumber daya dan jaringan yang selalu berubah sehingga membutuhkan algoritma yang tepat."

"Game theory merupakan algoritma yang mencari solusi permasalahan dengan menganalogikan masalah seperti permainan, kemudian diselesaikan dengan pendekatan matematis. Varian karakter dalam Game theory sangat beragam, dan pada perkembangannya selain diimplementasikan pada bidang sosial ekonomi, ternyata dapat diimplementasikan pada jaringan nirkabel. Pada penelitian ini Game theory dikembangkan dengan diimplementasikan pada jaringan sensor nirkabel sebagai metode optimasi . Jaringan sensor nirkabel sebagai pendukung sistem monitor membutuhkan dukungan jaringan yang andal dan stabil. Kondisi ini sangat membutuhkan ketersediaan energi. Karena keterbatasan ketersediaan energi maka semua proses bisnis jaringan harus dilakukan secara efektif dan efisien. Hal yang dilakukan adalah optimasi dengan pengelolaan jaringan yang baik. Optimasi yang dilakukan pada penelitian ini terkait dengan proses lokalisasi berbasis pengklasteran. Alasan pemilihan metode ini karena pengklasteran umumnya tidak memperhatikan permasalahan gangguan lingkungan terhadap sinyal, sementara lokalisasi adalah penempatan node dengan metode memanfaatkan informasi kekuatan sinyal yang diterima. Lokalisasi yang memanfaatkan informasi pengklasteran berupa konfigurasi sensor node berbasis ketersediaan energi, membantu proses pelacakan sensor node, karena dimulai dengan cluster head dengan tingkat ketersediaan energi yang lebih tinggi dibanding sensor node. Oleh karena itu, pada langkah selanjutnya, node yang dilacak dapat menjadi node referensi untuk node lain yang tidak diketahui. Game theory sebagai algoritma optimasi akan membantu menentukan koalisi anchor node. Pemilihan node sebagai anggota koalisi menggabungkan pendekatan geometris dengan Game theory. Konsep yang diusulkan ini akan divalidasi menggunakan simulator yang dibangun di atas platform Matlab. Akurasi adalah salah satu indikator kinerja lokalisasi, dan Root Mean Square Error (RMSE) dipilih sebagai parameter pengukuran untuk menunjukkan tingkat akurasi. Hasil simulasi menunjukkan bahwa jumlah sensor node mati dapat ditunda sekitar 1000 siklus jika dilakukan lokalisasi dengan Game theory. Hasil eksperimen menunjukkan bahwa kinerja jaringan cenderung meningkat setelah proses lokalisasi berbasis pengklasteran. Hal ini diindikasikan dengan peningkatan jumlah paket data yang dikirim dan masa hidup sensor node yang lebih lama. Hasil simulasi memvalidasi bahwa pada skenario pengujian pengiriman data terjadi peningkatan paket data yang dikirim sekitar 20%. Lokalisasi sendiri dalam implementasinya dapat mengalami kendala berupa interferensi . Interferensi sinyal radio dapat mengurangi akurasi hasil lokalisasi target node. Kondisi ini dapat mempengaruhi kualitas informasi yang diambil oleh sensor node terutama ketika jaringan mendukung sistem penginderaan jauh atau pemantauan yang nilai informasi sangat krusial. Gangguan ini timbul karena transmisi terjadi secara simultan pada suatu kanal transmisi, atau karena letak sensor yang kurang tepat. Oleh karena itu perlu dijadwalkan transmisi selama lokalisasi dan mengatur posisi anchor node. Pengaturan jadwal transmisi direpresentasikan dalam komputasi probabilitas transmisi node menggunakan pendekatan Game theory dengan mempertimbangkan energi sisa. Probabilitas transmisi untuk menghindari interferensi membentuk skema penjadwalan transmisi node. Komunikasi data yang lancar akan membuat kualitas proses lokalisasi baik. Hal ini ditandai dengan nilai RMSE yang rendah. Berdasarkan hasil eksperimen, probabilitas keberhasilan transmisi meningkat sekitar 20%. Terdapat korelasi yang kuat antara realibilitas dan parameter throughput.

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Game theory is an algorithm that overcomes problems by analogizing games and then solving them with a mathematical approach. Variants of characters in Game theory are very diverse, and in their development, apart from being implemented in the socio-economic field, it can actually be implemented in wireless networks. In this study, Game theory was developed and implemented on a wireless sensor network as an optimization method. Wireless sensor network as a monitoring system support requires reliable and stable network support. This condition really requires the availability of energy. Due to the limited energy availability, all network business processes must be carried out effectively and efficiently. What is done is optimization with good network management. The optimization carried out in this study is related to the clustering-based localization process. The reason for choosing this method is that clustering generally does not pay attention to environmental interference problems to the signal. Localization is the placement of nodes by utilizing the received signal strength information. Localization that utilizes clustering information in sensor node configurations based on energy availability helps the sensor node tracking process. This is because it starts with the cluster head with a higher energy availability level than the sensor node. Therefore, the tracked node can be a reference node for other unknown nodes in the next step. Game theory as an optimization algorithm will help determine the anchor node coalition. The selection of nodes as coalition members combines a geometric approach with Game theory. This proposed concept will be validated using a simulator built on the Matlab platform. Accuracy is an indicator of localization performance, and Root Mean Square Error (RMSE) was chosen as a measurement parameter to indicate the level of accuracy. The simulation results show that the number of dead sensor nodes can be delayed by approximate 1000 cycles if localization is carried out with Game theory. The experiment results show that network performance tends to increase after the clustering-based localization process. This is indicated by an increase in the number of data packets sent and a longer sensor node lifetime. The simulation results validate that there is an increase in data packets sent by about 20% in the data delivery test scenario. Localization itself in its implementation can experience obstacles in the form of interference. Radio signal interference can reduce the accuracy of the target node localization results. This condition can affect the quality of information retrieved by sensor nodes. This happens especially when the network supports remote sensing or monitoring systems where information is valuable. This disturbance arises because the transmission coincides on a transmission channel or the sensor is not located correctly. Therefore, it is necessary to schedule transmissions during localization and set anchor node positions. The transmission schedule arrangement is represented in the computation of the node transmission probability using a Game theory approach by considering the residual energy. The transmission probability of avoiding interference forms a node transmission scheduling scheme. Smooth data communication will make the quality of the localization process good. A low RMSE value characterizes it. Our experiments show that the probability of successful transmission increases by 20%, as shown by the graph. "

"This book offers an essential guide to Wireless Sensor Networks, IoT Security, Image Processing, Secure Information Systems, and Data Encryption. In addition, it introduces students and aspiring practitioners to the subject of destination marketing in a structured manner. It is chiefly intended for researcher students in the areas of Wireless Sensor Networks and Secure Data Communication (including image encryption, and intrusion detection systems), academics at universities and colleges, IT professionals, policymakers and legislators.Given its content, the book can be used as a reference text for both undergraduate and graduate studies, in courses on Wireless Sensor Networks, Secure Image Processing, and Data Encryption applications. The book is written in plain and easy-to-follow language and explains each main concept the first time it appears, helping readers with no prior background in the field. As such, it is a “must-read” guide to the subject matter."

"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%."

"Salah satu bagian dari proses pengambilan keputusan pada Jaringan Sensor Nirkabel (JSN) adalah pengiriman hipotesis dari sensor ke Pusat Informasi Gabungan (PIG). Konsumsi daya yang besar pada proses transmisi akan mengurangi waktu hidup sensor. Untuk mengatasi tantangan ini, penulis mengusulkan sebuah skenario transmisi on-off pada tiap sensor. Transmisi on ketika hipotesis sebelumnya tidak sama dengan hipotesis sekarang. Sebaliknya, transmisi off (tidak melakukan pengiriman) ketika hipotesis sebelumnya sama dengan hipotesis sekarang. Pengambilan keputusan di PIG menggunakan aturan Max-Log. Keunggulan aturan Max-Log adalah mempunyai probabilitas deteksi yang baik diseluruh nilai SNR dengan Pd0 0.84 pada Eb/E0 25 dB. Penelitian ini menghasilkan rumusan matematis aturan Max-Log yang menggabungkan dengan skenarion On-Off dalam rangka menghemat konsumsi daya. Pada hasil simulasi diperoleh selisih konsumsi daya sebesar 1,5 watt setelah observasi ke-10.

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One of the process decision making in wireless sensor network (WSN) is transmit hypothesis to fusion center. Having consumes high power on transmitting, it can reduce sensors life time. To solve this problem, author propose new scenario its called on-off transmission. Transmission on when sensor has different hypothesis than before. Contrary, transmission off when sensor has same hypothesis than before.

To make decision in fusion center, author use Max-Log fusion rules. The advantages of Max-Log fusion rule, it has good performace in all SNR value with Pd0 0.84 at Eb/E0 25 dB. The output of this research is mathematical approaches for Max-Log fusion rule combine with on-off scenario transmission. By simulation, Max-Log On-Off save energy consuming better than pure Max-Log with margin value 1,5 watt for 10 period observations."

"Saat ini terdapat beberapa protokol pada Application Layer yang berjalan di sistem Internet of Things. Protocol seperti MQTT, CoAP, XMPP, dan DDS memiliki arsitektur dan kinerja yang berbeda-beda. Pada jaringan sensor nirkabel yang memiliki daya rendah, bandwidth rendah dan reliabilitas yang terbatas lebih cocok menggunakan CoAP. Namun, CoAP menderita skalabilitas yang buruk jika dibandingkan dengan MQTT. Oleh sebab itu penelitian skripsi ini fokus pada implementasi CoAP Broker yang memungkinkan CoAP menggunakan arsitektur yang serupa dengan MQTT. Penelitian ini mengimplementasi Access Gateway dan beberapa skenario skalabilitas, meliputi skenario pemantauan sensor dan pengedalian aktuator pada peternakan ayam yang memiliki kandang ayam lebih dari satu. Hasil dari penelitian ini menunjukan keberhasilan mengimplementasi CoAP Broker beserta dengan skenario yang disebutkan dengan hasil evaluasi kinerja menunjukan latency yang belum menunjukan congestion saat menangani 130 permintaan per detik dan error-rate yang baik dengan nilai yang sangat rendah antara 0.01 - 0.04.

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Currently there are several Application Layer protocols running in Internet of Things system. Protocols such as MQTT, CoAP, XMPP, and DDS have different architectures and performance. For wireless sensor networks operating in low power, low bandwidth and with limited reliability, is more suitable to use CoAP. However, CoAP suffers from scalability problem which make it inferior to MQTT architecture. Therefore this research focuses on CoAP Broker implementation which enables MQTT like architecture to be implemented in CoAP.

This research aims to implement Access Gateway and several scalability scenarios, involving sensor monitoring scenarios and actuator controls on chicken farms that have more than one chicken coop. The results of this research shows the success of implementing CoAP Broker along with the mentioned scenarios with performance evaluation results show the latency which has not indicate any congestion when handling 130 requests per second and good error rate with very low value between 0.01 0.04."