Mengenal pasti masalah pemahaman dan hubungannya dengan latar belakang matematik, gaya pembelajaran, motivasi dan minat pelajar terhadap bab pengawalan kos makanan di Sekolah Menengah Teknik (ert) Rembau: satu kajian kes.

Kajian ini dijalankan untuk mengkaji hubungan korelasi antara latar belakang Matematik, gaya pembelajaran, motivasi dan minat dengan pemahaman pelajar terhadap bab tersebut. Responden adalah seramai 30 orang iaitu terdiri daripada pelajar tingkatan lima kursus Katering, Sekolah Menengah Teknik (ERT) Rembau, Negeri Sembilan. Instrumen kajian adalah soal selidik dan semua data dianalisis menggunakan program SPSS versi 10.0 untuk mendapatkan nilai min dan nilai korelasi bagi memenuhi objektif yang telah ditetapkan. Hasil kajian ini menunjukkan bahawa hubungan korelasi antara gaya pembelajaran pelajar terhadap pemahaman pelajar adalah kuat. Manakala hubungan korelasi antara latar belakang Matematik, motivasi dan minat terhadap pemahaman pelajar adalah sederhana. Nilai tahap min bagi masalah pemahaman pelajar, latar belakang Matematik, gaya pembelajaran, motivasi dan minat terhadap bab Pengawalan Kos Makanan adalah sederhana. Kajian ini mencadangkan penghasilan satu Modul Pembelajaran Kendiri bagi bab Pengawalan Kos Makanan untuk membantu pelajar kursus Katering dalam proses pembelajaran mereka

SDL based validation of a node monitoring protocol

Mobile ad hoc network is a wireless, self-configured, infrastructureless network of mobile nodes. The nodes are highly mobile, which makes the application running on them face network related problems like node failure, link failure, network level disconnection, scarcity of resources, buffer degradation, and intermittent disconnection etc. Node failure and Network fault are need to be monitored continuously by supervising the network status. Node monitoring protocol is crucial, so it is required to test the protocol exhaustively to verify and validate the functionality and accuracy of the designed protocol. This paper presents a validation model for Node Monitoring Protocol using Specification and Description Llanguage (SDL) using both Static Agent (SA) and Mobile Agent (MA). We have verified properties of the Node Monitoring Protocol (NMP) based on the global states with no exits, deadlock states or proper termination states using reachability graph. Message Sequence Chart (MSC) gives an intuitive understanding of the described system behavior with varying node density and complex behavior etc.Comment: 16 pages, 24 figures, International Conference of Networks, Communications, Wireless and Mobile 201

Node placement optimization using extended virtual force and cuckoo search algorithm in wireless sensor network

Node placement is one of the fundamental issues that affects the performance of coverage and connectivity in Wireless Sensor Network (WSN). In a large scale WSN, sensor nodes are deployed randomly where they are scattered too close or far apart from each other. This random deployment causes issues such as coverage hole, overlapping and connectivity failure that contributes to the performance of coverage and connectivity of WSN. Therefore, node placement model is develop to find the optimal node placement in order to maintain the coverage and guaranteed the connectivity in random deployment. The performance of Extended Virtual Force-Based Algorithm (EVFA) and Cuckoo Search (CS) algorithm are evaluated and EVFA shows the improvement of coverage area and exhibits a guaranteed connectivity compared to CS algorithm. Both algorithms have their own strength in improving the coverage performance. The EVFA approach can relocate the sensor nodes using a repulsive and attractive force after initial deployment and CS algorithm is more efficient in exploring the search of maximum coverage area in random deployment. This study proposed Extended Virtual Force and Cuckoo Search (EVFCS) algorithm with a combination of EVFA and CS algorithm to find an optimal node placement. A series of experimental studies on evaluation of proposed algorithm were conducted within simulated environment. In EVFCS, the algorithm searches the best value of threshold distance and relocated the new position of sensor nodes. The result suggested 18.212m is the best threshold distance that maximizes the coverage area. It also minimizes the problems of coverage hole and overlapping while guaranteeing a reasonable connectivity quality. It proved that the proposed EVFCS outperforms the EVFA approach and achieved a significant improvement in coverage area and guaranteed connectivity. The implementation of the EVFCS improved the problems of initial random deployment

PERFORMANCE ANALYSIS AND OPTIMIZATION OF QUERY-BASED WIRELESS SENSOR NETWORKS

This dissertation is concerned with the modeling, analysis, and optimization of large-scale, query-based wireless sensor networks (WSNs). It addresses issues related to the time sensitivity of information retrieval and dissemination, network lifetime maximization, and optimal clustering of sensor nodes in mobile WSNs. First, a queueing-theoretic framework is proposed to evaluate the performance of such networks whose nodes detect and advertise significant events that are useful for only a limited time; queries generated by sensor nodes are also time-limited. The main performance parameter is the steady state proportion of generated queries that fail to be answered on time. A scalable approximation for this parameter is first derived assuming the transmission range of sensors is unlimited. Subsequently, the proportion of failed queries is approximated using a finite transmission range. The latter approximation is remarkably accurate, even when key model assumptions related to event and query lifetime distributions and network topology are violated. Second, optimization models are proposed to maximize the lifetime of a query-based WSN by selecting the transmission range for all of the sensor nodes, the resource replication level (or time-to-live counter) and the active/sleep schedule of nodes, subject to connectivity and quality-of-service constraints. An improved lower bound is provided for the minimum transmission range needed to ensure no network nodes are isolated with high probability. The optimization models select the optimal operating parameters in each period of a finite planning horizon, and computational results indicate that the maximum lifetime can be significantly extended by adjusting the key operating parameters as sensors fail over time due to energy depletion. Finally, optimization models are proposed to maximize the demand coverage and minimize the costs of locating, and relocating, cluster heads in mobile WSNs. In these models, the locations of mobile sensor nodes evolve randomly so that each sensor must be optimally assigned to a cluster head during each period of a finite planning horizon. Additionally, these models prescribe the optimal times at which to update the sensor locations to improve coverage. Computational experiments illustrate the usefulness of dynamically updating cluster head locations and sensor location information over time

Relocating sensor nodes to maximize cumulative connected coverage in wireless sensor networks

PubMed ID: 27879850In order to extend the availability of the wireless sensor network and to extract maximum possible information from the surveillance area, proper usage of the power capacity of the sensor nodes is important. Our work describes a dynamic relocation algorithm called MaxNetLife, which is mainly based on utilizing the remaining power of individual sensor nodes as well as properly relocating sensor nodes so that all sensor nodes can transmit the data they sense to the sink. Hence, the algorithm maximizes total collected information from the surveillance area before the possible death of the sensor network by increasing cumulative connected coverage parameter of the network. A deterministic approach is used to deploy sensor nodes into the sensor field where Hexagonal Grid positioning is used to address and locate each sensor node. Sensor nodes those are not planned to be actively used in the close future in a specific cell are preemptively relocated to the cells those will be in need of additional sensor nodes to improve cumulative connected coverage of the network. MaxNetLife algorithm also includes the details of the relocation activities, which include preemptive migration of the redundant nodes to the cells before any coverage hole occurs because of death of a sensor node. Relocation Model, Data Aggregation Model, and Energy model of the algorithm are studied in detail. MaxNetLife algorithm is proved to be effective, scalable, and applicable through simulations.Publisher's Versio