Optimization Algorithms for Joint Power and Sub-Channel Allocation for NOMA-Based Maritime Communications

This paper investigates resource optimization schemes in a marine communication scenario based on non-orthogonal multiple access (NOMA). According to the offshore environment of the South China Sea, we first establish a Longley–Rice-based channel model. Then, the weighted achievable rate (WAR) is considered as the optimization objective to weigh the information rate and user fairness effectively. Our work introduces an improved joint power and user allocation scheme (RBPUA) based on a single resource block. Taking RBPUA as a basic module, we propose three joint multi-subchannel power and marine user allocation algorithms. The gradient descent algorithm (GRAD) is used as the reference standard for WAR optimization. The multi-choice knapsack algorithm combined with dynamic programming (MCKP-DP) obtains a WAR optimization result almost equal to that of GRAD. These two NOMA-based solutions are able to improve WAR performance by 7.47% compared with OMA. Due to the high computational complexity of the MCKP-DP, we further propose a DP-based fully polynomial-time approximation algorithm (DP-FPTA). The simulation results show that DP-FPTA can reduce the complexity by 84.3% while achieving an approximate optimized performance of 99.55%. This advantage of realizing the trade-off between performance optimization and complexity meets the requirements of practical low-latency systems.

Secure message transmission scheme in wireless sensor networks

Wireless sensor networks (WSNs) have been the subject of intensive research in the past few years and the backbone of most maximum present information technology. WSNs have been employed in various applications such as track monitoring battlegrounds in military fields and patients’ medical requirements in the civilian field. The wireless sensor networks are always randomly distributed in an open area (hostile), pervasive environment, and open media channel. Thus, WSNs are vulnerable to several species of attacks. Moreover, messages may be easily intercepted or altered because the transmission is not secure, hence effective key management scheme is strongly needed to reduce the risks. Cryptography methods are a crucial aspect of WSNs to reach security goals. In this paper, we propose an efficient and secure message transmission scheme that combines the Knapsack algorithm with the Diffie-Hellmann process to encrypt messages. The results and analysis show that the proposed scheme is efficient and it achieves most of the security goals providing high privacy and security. It is also resilient against some of the well-known attacks.

Energy-Efficient Distributed Packet Scheduling Optimization Strategy in Cooperative Vehicle Infrastructure Systems

In the cooperative vehicle infrastructure system (CVIS), due to the limitation of deployment conditions, some roadside units (RSUs) need to use renewable energy to supply power and transmit the fused sensor network’s data to the backbone network through the passing vehicles. Aiming at the problem of energy consumption and time delay guarantee of multiple self-powered RSUs in the CVIS, a distributed packet scheduling optimization strategy for energy-delay trade-off in self-powered RSUs is proposed. The strategy can minimize the system energy consumption by constraining the packet queue length of the self-powered RSUs. A dynamic optimization model of distributed packet adaptive scheduling for multiple self-powered RSUs is established based on the Lyapunov optimization theory. Based on the knapsack algorithm, the analytical algorithm of the optimization model is proposed. The simulation results show that the packet scheduling strategy can reduce the energy consumption and delay of the system by satisfying the upper limit of the packet queue length.

Queries Processing in Wireless Sensor Network

For the super-excellence applications used to control the water level in rivers, temperature handles a very large volume of information and does not stop constantly changing. These spatio-temporal data collected by a network of sensors form a set of thematic, integrated, non-volatile and historical data organized to help decision-making. Usually this process is performed with temporal, spatial and spatiotemporal queries. This in turn increases the execution time of the query load. In the literatures, several techniques have been identified such as materialized views (MV), indexes, fragmentation, scheduling, and buffer management. These techniques do not consider the update of the request load and the modification at the database level. In this chapter, we propose an optimal dynamic selection solution based on indexes and VMs. the solution is optimal when it meets the entire workload with a reasonable response time. The proposed approach supports modification at the database level and at the workload level to ensure the validity of the optimal solution for this the knapsack algorithm was used.

Implementasi Algoritma Merkle-Hellman Knapsack dalam Penyandian Record Database

A lot of data is misused without the data owner being aware of it. Software developers must ensure the security user data on their system. Due to the size of the market that houses data, the security of record databases must be of great concern. Cryptographic systems or data encryption can be used for data security. The Merkle-Hellman Knapsack algorithm is included in public-key cryptography because it uses different keys for the encryption and decryption processes. This algorithm belongs to the NP-complete algorithm which cannot be solved in polynomial order time. This algorithm has stages of key generation, encryption, and decryption. The results of this study secure database records from theft by storing records in the form of ciphertext/password. Ciphertext generated by algorithmic encryption has a larger size than plaintext.

A novel superframe structure and optimal time slot allocation algorithm for IEEE 802.15.4–based Internet of things

IEEE 802.15.4 standard is specifically designed for a low-rate and low-processing Internet of things (IoT) applications and offers guaranteed time slots. A beacon-enabled IEEE 802.15.4 consists of a superframe structure that comprises of the contention access period and contention-free period. During contention-free period, nodes transfer their data using guaranteed time slots without any collision. The coordinator node receives data transmission requests in one cycle and allocates guaranteed time slots to the nodes in the next cycle. This allocation process may cause large delay that may not be acceptable for few applications. In this work, a novel superframe structure is proposed that significantly reduces guaranteed time slots allocation delay for the nodes with data requests. The proposed superframe structure comprises of two contention access periods and one contention-free period, where contention-free period precedes both contention access periods with reduced slot size. In addition, the knapsack algorithm is modified for better guaranteed time slots allocation by allowing more guaranteed time slots requesting nodes to send their data as compared to the IEEE 802.15.4 standard. The simulation and analytical results show that the proposed superframe structure reduces the network delay by up to 80%, increases contention-free period utilization up to 50%, and allocates guaranteed time slots up to 16 nodes in a single superframe duration.