Certificate Path Discovery by Constructing VirtualHierarchy to Administer Trust Relationship using Peer toPeer PKI in MANETs

In the scenario with many small base stations (SBSs) deployed, edge caching technology could bring contents closer to users by caching files at SBSs. Considering these SBSs with limited storage capacity, how to effectively cache files is a difficult and interesting problem. Many factors should be considered, such as the popularity of files, user download delay and average hit rate. In this paper, we investigate this problem and propose a minimizing user download delay caching (MUDDC) algorithm. It decides which files should be cached and where to cache them for reducing download delay. There is a conflict between hit rate and download delay with the limited SBS storage capacity. We target the average user download delay and model an optimization problem with the constraint of average hit rate and find the optimal solution. The simulation results show that the system performance is improved.

The aim of this paper is to present mixed integer linear programming formulations for the production routing problem with backordering (PRP-B) and a new hybrid heuristic to solve the problem. The PRP-B is considered in the context of a supply chain consisting of a production facility with limited production and storage capacities and geographically dispersed points of sale with limited storage capacities. The PRP-B integrates multiple item lot sizing decisions and vehicle routing decisions to the points of sale, where backordering of end customer demands is allowed at a penalty. Two integrated mixed integer programming models are formulated and a solution procedure consisting of a relax-and-fix heuristic combined with a local search algorithm is proposed. The numerical results show that this hybrid heuristic outperforms a state-of-the-art MIP commercial solver, in terms of solution quality and CPU times.

The main purpose of this paper wants to investigate the effect of trade credit policy with limited storage capacity within the economic order quantity (EOQ) framework. Goyal is frequently cited when the inventory systems under conditions of permissible delay in payments are discussed. But Goyal assumed that the retailer’s storage capacity is unlimited. This assumption is debatable. So, we want to extend Goyal’s model to the case that the retailer’s storage capacity is limited. Then, two theorems present solution procedures to locate the optimal cycle times of the annual total relevant cost function. In essence, the inventory model discussed in this paper generalizes that of Goyal. Finally, numerical examples are given to illustrate all theorems obtained in this paper.

In this paper, we investigate downlink transmissions in a wireless communication system enabled by a swarm of unmanned aerial vehicles (UAVs) which are spatially dispatched to cooperatively deliver requested contents to ground users. First, we propose a communication scheme that exploits the flexible deployment of UAVs as well as their cooperative transmissions to improve in-network user admission. Unlike previous literature, a practical operational constraint of limited storage capacity for UAVs is considered. Then, from the knowledge that cooperation among UAVs depends on the availability of the contents in their limited storage space, we propose a novel joint optimization problem to determine the content placement, location planning, user admission decision and transmit beamforming to maximize the number of users experiencing a minimum required rate, so-called admitted users. Since the formulated problem is a mixed-integer non-linear program which is generally non-deterministic polynomial-time hard, we proposed a framework that is developed on the basis of difference-of-convex (DC) programming to transform the original problem into a series of approximate convex problems which can be iteratively solved until convergence. Our extensive simulation results reveal that the proposed scheme outperforms other schemes that have been introduced in previous work and reflect a notable trend that deploying more cooperative UAVs with fewer resources (power and storage capacity) is more efficient than deploying fewer UAVs with more resources. In particular, in one of our collected results, the total communication power can be reduced by roughly 40 dB when doubling the number of cooperative UAVs.

Researches on routing and traffic have provided a general way of network dynamics simulation. However, these works usually fix the processing capacity of network elements and ignore the relationship between the processing capacity and storage capacity. This paper introduces a multi-layer network model coupled with Macroscopic Fundamental Diagram (MFD) to couple these two capacities. Percolation on the model has been employed revealing that adjustable parameters such as selection coefficient, storage capacity and dumping coefficient have different effects on the robustness and functionality of our model. And result also shows that the robustness and functionality are contradictory on the model.

This paper presents a comprehensive risk-averse multistage model for dealing with the design and planning problem of a closed-loop supply chain (CLSC) considering adjustments in the supply chain structure during the planning horizon as well as uncertainty in supply and customer demands. The stochastic approach addresses a problem of a generic multiperiod multiproduct CLSC with a general network structure of ten types of entities, risk-averse objectives associated with both costs and revenues, a flexible network structure, transport capacity, salvage grade of returned products, CO2 emissions of the transport system, as well as minimum and maximum storage and processing capacity limits for network entities. A key aspect of the proposed work is to cope with a multiobjective function where the maximization of the expected profit is combined with the fundamental idea of risk management incorporated through the explicit trade-off between risk associated with costs and revenues. To the authors' knowledge, the joining of the considerations of risk management and aspects related to the opening/closing of entities during the planning horizon in a multistage stochastic context has not yet been considered. With the objective of achieving more reliable solutions, five objective functions that include risk-averse criteria are considered. A sensitivity analysis of the approach performance considering changes in the parameters associated with the risk metrics is conducted. Variations in the relevance of the risk quantification are carried out in order to show the trade-off between solution quality and handling of uncertainty.

Smart city refers to the information system with Internet of things and cloud computing as the core technology and government management and industrial development as the core content, forming a large-scale, heterogeneous and dynamic distributed Internet of things environment between different Internet of things. There is a wide demand for cooperation between equipment and management institutions in the smart city. Therefore, it is necessary to establish a trust mechanism to promote cooperation, and based on this, prevent data disorder caused by the interaction between honest terminals and malicious terminals. However, most of the existing research on trust mechanism is divorced from the Internet of things environment, and does not consider the characteristics of limited computing and storage capacity and large differences of Internet of things devices, resulting in the fact that the research on abstract trust mechanism cannot be directly applied to the Internet of things; On the other hand, various threats to the Internet of things caused by security vulnerabilities such as collision attacks are not considered. Aiming at the security problems of cross domain trusted authentication of Intelligent City Internet of things terminals, a cross domain trust model (CDTM) based on self-authentication is proposed. Unlike most trust models, this model uses self-certified trust. The cross-domain process of internet of things (IoT) terminal can quickly establish a trust relationship with the current domain by providing its trust certificate stored in the previous domain interaction. At the same time, in order to alleviate the collision attack and improve the accuracy of trust evaluation, the overall trust value is calculated by comprehensively considering the quantity weight, time attenuation weight and similarity weight. Finally, the simulation results show that CDTM has good anti collusion attack ability. The success rate of malicious interaction will not increase significantly. Compared with other models, the resource consumption of our proposed model is significantly reduced.

Currently, refined petroleum products are manufactured by six refineries in South Africa. The supply of refined petroleum products is supplemented by imports of refined petroleum products. These refined petroleum products are transported by pipeline, rail, road, sea and a combination thereof to depots across the country. These products are then distributed directly to commercial customers through points of resale in the form of retail service stations. The challenge is that the storage facilities and distribution networks in South Africa are currently utilised to its full capacity. There is a need to expand current storage infrastructure or to erect new storage facilities to facilitate imports. Durban Port that currently handles 70% of the country’s crude oil and 40% of refined products is also utilised to its full capacity. The investigated problem pertains to the limited storage and transport capacity available for the distribution of petroleum products in the country. The interview protocol, which was based on the literature reviewed, was used for compiling the primary data for the case study. Selected findings revealed that the respondents perceived that storage capacity is the most significant constraint militating against adequate supply by the supply chain. The findings also indicated that the respondents were of the opinion that transport rates and routes (cost of logistics) are the greatest contributor to the prices of products. As a result, there appears to be a major scope for improvement in terms of the usage of pipelines and rails for the movement of petroleum products.Keywords: Petroleum products, storage facilities, supply chain, transportation, South African energy sector.Disciplines: civil engineering, architecture, business studies, energy studies

With increasing demand on digital images, there is a need to compress the image to entertain the limited bandwidth and storage capacity. Recently, there is a growing interest among researchers focusing on compression of various types of images and data. Amongst various compression algorithms, transform-based compression is one of the promising algorithms. Despite the technological advances in transmission and storage, the demands placed on the bandwidth of communication and storage capacities by far outstrips its availability. This paper presents a review of image compression principle, compression techniques and various thresholding algorithms (pre-processing algorithms) and quantization algorithm (post-processing algorithms). This paper intends to give an overview to the relevant parties to choose the suitable image compression algorithms to suit with the need.

This thesis attempts to look at the inventory management practices of a relatively new company that has shown progress in its operations. The business of the case company is trading. The main job involves analyzing relevant historical documents over the 10 months from May 2007 to February 2008 to cover the fluctuation of demand. The company’s products are divided into 3 categories to facilitate analysis, and eventually to select only the most important category for detailed study. The imported products with known price increases turned out to have the most value and were of the most importance to the company. The Known Price Increase Model was then modified and applied to these products to serve as the basis for considering the stocks that had to be ordered for storage in order to optimize return on investment. The conventional Fixed Order Quantity Model was used for the products the prices of which do not change frequently. As the case company has 2 warehouses that are situated apart, and have limited storage capacity, it was studied the ratio of the products for storage at the 2 warehouses to increase efficiency and better management control. When an attempt to determine the quantities of all the products under study that have to be ordered and stocked in the inventory was carried out, it was discovered that the company did not have sufficient storage capacity for all of them, namely, the storage capacity needed was 8,421.88 cubic meters but the storage capacity available in warehouse A is only 1,750 cubic meters. This shortfall is not unusual, especially since this company is quite new and could reasonably be expected to be cautious in its operations. The study shows that the total savings from using the Fixed Order Quantity Model for all the unclassified products is 44,594.93 baht, or equal to 7.89 per cent of the Total Stocking Cost (TSC). The savings from applying the Known Price Increase Model to imported products and domestic products with known price increases products is 594,512.30 baht

A Stylized Model of the Oil Squeeze

Wireless nodes are one of the main components in different applications that are offered in a smart city. These wireless nodes are responsible to execute multiple tasks with different priority levels. As the wireless nodes have limited processing capacity, they offload their tasks to cloud servers if the number of tasks exceeds their task processing capacity. Executing these tasks from remotely placed cloud servers causes a significant delay which is not required in sensitive task applications. This execution delay is reduced by placing fog computing nodes near these application nodes. A fog node has limited processing capacity and is sometimes unable to execute all the requested tasks. In this work, an optimal task offloading scheme that comprises two algorithms is proposed for the fog nodes to optimally execute the time-sensitive offloaded tasks. The first algorithm describes the task processing criteria for local computation of tasks at the fog nodes and remote computation at the cloud server. The second algorithm allows fog nodes to optimally scrutinize the most sensitive tasks within their task capacity. The results show that the proposed task execution scheme significantly reduces the execution time and most of the time-sensitive tasks are executed.

The world has recently witnessed a rapid revolution in multimedia signal processing.Images are one of the most widely used media that need a large amount of data to be represented.Because of the restrictions of limited bandwidth and storage capacity, image compression is a necessity.AMBTC is a straightforward lossy image compression scheme, and studies are still being conducted to improve its performance.This paper incorporated AMBTC with block classification and artificial neural networks to lower the bitrate and preserve the image quality.The proposed scheme was benchmarked with the recent AMBTC techniques for greyscale images.According to the results, the proposed method significantly improved over conventional AMBTC by achieving 16% bitrate reduction while preserving 99.19% of AMBTC's Peak Signal to Noise Ratio (PSNR).

Mobile multimedia applications have become an integral part of modern digital life, offering services such as video streaming, online gaming, virtual reality, and real-time communication. Despite their growing popularity, these applications face inherent challenges due to the limited computational resources, storage capacity, and battery life of mobile devices. Cloud computing has emerged as a transformative solution, providing scalable processing power, extensive storage, and on-demand services. This paper presents a theoretical study on the performance evaluation of mobile multimedia applications in cloud computing environments. The study focuses on key performance metrics including latency, throughput, energy consumption, scalability, and quality of service (QoS). By critically analyzing the impact of cloud integration on mobile multimedia applications, this research identifies the benefits, limitations, and optimization strategies required to improve application performance. The findings highlight the significance of cloud-based architectures, task offloading, and adaptive resource management in achieving efficient and reliable mobile multimedia services.

Assessment and identification of human activity and posture with triaxial accelerometer can provide information about the health state and the chronic care. This paper proposes a human state recognition algorithm based on Kalman filter (SRKF), which could identify steady state and state transition in real time. In this study, an automatic state-recognition system consisting of a Bluetooth module and a smart phone is developed. The Bluetooth module with a triaxial accelerometer was placed on the body and the raw sensor data was transported to and processed on the smart phone. Associated kinematics characteristic of human activity and the accelerometer signal, the results of amplitude function of vector CSVM were processed by Kalman filter to identify human state. Data were collected from ten adults in unsupervised environment. Experiment result shows that the algorithm has achieved better performance on the smart phone with limited computing and storage capacity.