Secrecy outage performance analysis for energy harvesting sensor networks with a jammer using relay selection strategy

In this paper, we study radio frequency energy harvesting (EH) in a wireless sensor network in the presence of multiple eavesdroppers (EAVs). Specifically, the sensor source and multiple sensor relays harvest energy from multiple power transfer stations (PTSs), and then, the source uses this harvested energy to transmit information to the base station (BS) with the help of the relays. During the transmission of information, the BS typically faces a risk of losing information due to the EAVs. Thus, to enhance the secrecy of the considered system, one of the relays acts as a jammer, using harvested energy to generate interference with the EAVs. We propose a best-relay-and-best-jammer scheme for this purpose and compare this scheme with other previous schemes. The exact closed-form expression for the secrecy outage probability (SOP) is obtained and is validated through Monte Carlo simulations. A near-optimal EH time algorithm is also proposed. In addition, the effects on the SOP of key system parameters such as the EH efficiency coefficient, the EH time, the distance between the relay and BS, the number of PTSs, the number of relays, and the number of EAVs are investigated. The results indicate that the proposed scheme generally outperforms both the best-relay-and-random-jammer scheme and the random-relay-and-best-jammer scheme in terms of the secrecy capacity

Throughput Optimization for NOMA Energy Harvesting Cognitive Radio with Multi-UAV-Assisted Relaying under Security Constraints

This paper investigates the throughput of a non-orthogonal multiple access (NOMA)-based cognitive radio (CR) system with multiple unmanned aerial vehicle (UAV)-assisted relays under system performance and security constraints. We propose a communication protocol that includes an energy harvesting (EH) phase and multiple communication phases. In the EH phase, the multiple UAV relays (URs) harvest energy from a power beacon. In the first communication phase, a secondary transmitter (ST) uses the collected energy to send confidential signals to the first UR using NOMA. Simultaneously, a ground base station communicates with a primary receiver (PR) under interference from the ST. In the subsequent communication phases, the next URs apply the decode-and-forward technique to transmit the signals. In the last communication phase, the Internet of Things destinations (IDs) receive their signals in the presence of an eavesdropper (EAV). Accordingly, the outage probability of the primary network, the throughput of the secondary network, and the leakage probability at the EAV are analyzed. On this basis, we propose a hybrid search method combining particle swarm optimization (PSO) and continuous genetic algorithm (CGA) to optimize the UR configurations and the NOMA power allocation to maximize the throughput of the secondary network under performance and security constraints

Optimization of Cluster Web Server Scheduling from Site Access Statistics

In order to satisfy high volume of site accesses, cluster of web servers have been widely deployed by many popular web sites. This paper reviews a number of parallel web server architectures and proposes a method for calculating the server scheduling weights for efficient cluster performance by taking into consideration the web site’s access statistics. Conventionally, equal weights are used for homogeneous cluster of web servers which have identical hardware configuration. However, for many web sites, the cluster is constructed with new servers being added as the site slowly gains popularity. As hardware architecture changes over time, these sites tend to end up with a heterogeneous cluster with servers of different hardware configuration. In order to obtain the optimal overall performance, the scheduling weights for such a heterogeneous cluster must be carefully calculated to maximize the performance of each server. Traditionally, the server performance is measured using benchmarks. In this paper, CPU benchmark and Disk I/O benchmark are used as base parameters for weights calculation. A typical web site consists of both static pages, which are I/O-bounded, and dynamic pages, which are CPU-bounded. We will make use of statistical data from site access log to identify the ratio of static load to dynamic load. Finally the server performance is obtained from the summation of CPU benchmark and Disk I/O benchmark, adjusted with respect to this ratio. Experiments were carried out on a cluster of three heterogeneous servers. Results showed that our method offer significant amount of cluster performance gains in comparison with the use of CPU or Disk I/O benchmark alone

Network-based Intrusion Detection Model for Detecting TCP SYN flooding

This paper presents a method for detecting TCP SYN flooding attack using BENEF model. Our model relies on the significant parameters of anomalous network packets, the statistic of system behavior, and the decision with threshold and fuzzy rule-based technique. With fuzzy technique, rules or a set of rules corresponding with the appropriate membership value are designed for analysis and to find the final decision. Our first prototype employs BENEF model to implement the network-based intrusion detection system. Current implementation is experiment with TCP SYN flooding attacks

Data Partition and Job Scheduling Technique for Balancing Load in Cluster of Web Spiders

Search engines primary rely on web spiders to collect large amount of data for indexing and analysis. Data collection can be performed by several agents of web spiders running in parallel or distributed manner over a cluster of workstations. This parallelization is often necessary in order to cope with a large number of pages in a reasonable amount of time. However, while keeping a good parallelism, too many requests should not send from nodes to the same web server in a short period of time. In the environment of a cluster of web spiders, it requires an effective synchronization and scheduling technique between nodes in the cluster. In this paper, we propose a method of URL partition among the node of cluster running web spider and a scheduling technique to dispatch URLs to spider’s thread using a simple but efficient URLs scramble. Our approach guarantees that only one node in the cluster can contact a web server in a time, i.e., avoid overloading remote web servers

On an Evaluation of Network Intrusion Dispersion

Abstract. The widespread of Internet worms is an issue of concern. A worm program tries to compromise systems in a large scale network. To handle the disaster proactively, it is very essential to evaluate the worm dispersion. We propose an evaluation model for the network intrusion dispersion on a spread of worms. The model scrutinizes important factors from a network infrastructure then calculates the dispersion value by using a rule-based fuzzy technique. These significant factors are generated from an analysis of trust relationship on nodes, the visibility of nodes, and the homogeneity of systems. The output of the model can be used to estimate the severity of the worm dispersion effectively.

Explicit Rate Adjustment (ERA): Responsiveness, Network Utilization Efficiency and Fairness for Layered Multicast

To provide layered multicast with responsiveness, efficiency in network utilization, scalability and fairness (including inter-protocol fairness, intra-protocol fairness, intra-session fairness and TCP-friendliness) for layered multicast, we propose in this paper a new multicast congestion control, called Explicit Rate Adjustment (ERA). Our protocol uses an algorithm relying on TCP throughput equation and Packet-bunch Probe techniques to detect optimal bandwidth utilization; then adjusts the reception rate accordingly. We have built ERA into a network simulator (ns2) and demonstrate via simulations that the goals are reached