Packet Reordering Metrics to Enable Performance Comparison in IP-NetworksRead the full article
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An Exponential Active Queue Management Method Based on Random Early Detection
Congestion is a key topic in computer networks that has been studied extensively by scholars due to its direct impact on a network’s performance. One of the extensively investigated congestion control techniques is random early detection (RED). To sustain RED’s performance to obtain the desired results, scholars usually tune the input parameters, especially the maximum packet dropping probability, into specific value(s). Unfortunately, setting up this parameter into these values leads to good, yet biased, performance results. In this paper, the RED-Exponential Technique (RED_E) is proposed to deal with this issue by dropping arriving packets in an exponential manner without utilizing the maximum packet dropping probability. Simulation tests aiming to contrast E_RED with other Active Queue Management (AQM) methods were conducted using different evaluation performance metrics including mean queue length (), throughput (), average queuing delay (), overflow packet loss probability (), and packet dropping probability (). The reported results showed that E_RED offered a marginally higher satisfactory performance with reference to and than that found in common AQM methods in cases of heavy congestion. Moreover, RED_E compares well with the considered AQM methods with reference to the above evaluation performance measures using minimum threshold position () at a router buffer.
Delay Testing Method for Off-Site Asynchronous LTE Networks Based on Singular Value Removal
This paper presents an experimental campaign of transmission delay measurements under asynchronous condition for the communication-based train control (CBTC) systems. A three-stage asynchronous clock correction method is proposed. Before and after the working stage, the clock difference between transmitter and the receiver is calculated, moreover the relative offset and relative skew between two terminals of the working stage are derived, and it further leads towards the experimental verification of the transmission delay. In order to improve the measurement accuracy, the singular values are distinguished and eliminated in the test. Using this method, the transmission delay of the Long-Term Evolution for Metro (LTE-M) communication between the train and the signalling room in Shanghai Zhangjiang Metro Training Line is measured successfully, which demonstrates the effectiveness of the proposed one-way transmission delay test.
A Proficient Bee Colony-Clustering Protocol to Prolong Lifetime of Wireless Sensor Networks
In wireless sensor network, replacement of node’s battery is very tough task in hostile environments. Therefore, to maximize network lifetime is the ultimate solution. Dividing the sensing region of wireless sensor network into clusters is an excellent approach to gain high energy efficiency and to enhance lifetime of the network. On the other hand, heads of the cluster need additional energy because of additional work such as obtaining data from its member nodes, aggregation of their data, and finally sending it to the base station. To enhance the lifetime of these networks, proper selection of heads plays a vital role. In this paper, we propose proficient bee colony-clustering protocol (PBC-CP) which is based on artificial bee colony algorithm. In PBC-CP approach, we have taken important factors for selection of heads such as node’s energy, degree of node, and distance from base station to node. For transmitting the data from cluster head to base station, it chooses the energy-efficient path which further minimizes the energy consumption of sensor network. Simulation experiments show the effectiveness of our proposed approach.
New Courteous Algorithm for Uplink Scheduling in LTE-Advanced and 5G Networks
The fast evolution of the number of wireless users and the emergence of new multimedia services have motivated third-generation partnership project (3GPP) to develop new radio access technologies. Thus, the carrier aggregation (CA) was introduced from version 10 long-term evolution (LTE), known as long-term evolution-advanced (LTE-A), to meet the increasing demands in terms of throughput and bandwidth and to ensure the Quality of Service (QoS) for different classes of bearers in LTE networks. However, such solution stills inefficient until implementing good resources management scheme. Several scheduling mechanisms have been proposed in the literature, to guarantee the QoS of different classes of bearers in LTE-A and 5G networks. Nevertheless, most of them promote high-priority bearers. In this study, a new approach of uplink scheduling resources has been developed. It aims to ensure service fairness of different traffic classes that allocates bearers over LTE-A and 5G networks. Also, it raises the number of admitted users in the network by increasing the number of admitted bearers through a dynamic management of service priorities. In fact, the low-priority traffic classes, using low-priority bearers, are favoured during a specific time interval, based on the average waiting time for each class. Simulation results show that the QoS parameters were much improved for the low-priority classes without significantly affecting the QoS of high priority ones.
Hybrid Botnet Detection Based on Host and Network Analysis
Botnet is one of the most dangerous cyber-security issues. The botnet infects unprotected machines and keeps track of the communication with the command and control server to send and receive malicious commands. The attacker uses botnet to initiate dangerous attacks such as DDoS, fishing, data stealing, and spamming. The size of the botnet is usually very large, and millions of infected hosts may belong to it. In this paper, we addressed the problem of botnet detection based on network’s flows records and activities in the host. Thus, we propose a general technique capable of detecting new botnets in early phase. Our technique is implemented in both sides: host side and network side. The botnet communication traffic we are interested in includes HTTP, P2P, IRC, and DNS using IP fluxing. HANABot algorithm is proposed to preprocess and extract features to distinguish the botnet behavior from the legitimate behavior. We evaluate our solution using a collection of real datasets (malicious and legitimate). Our experiment shows a high level of accuracy and a low false positive rate. Furthermore, a comparison between some existing approaches was given, focusing on specific features and performance. The proposed technique outperforms some of the presented approaches in terms of accurately detecting botnet flow records within Netflow traces.
Towards Developing Enhanced Cluster-Based QoS-Aware Routing in MANET
Creating dynamic communication infrastructures between mobile devices and satisfying the desires for time-sensitive multimedia applications have introduced new challenges in the design of protocols for mobile ad hoc networks. In this paper, to stream time-sensitive applications using mobile ad hoc network (MANET), we have selected the Optimal Link State Routing (OLSR) protocol. However, the protocol has high overhead because each node selects a set of multipoint relay (MPR) nodes. Therefore, we have proposed quality of service (QoS) supporting the MPR selection approach and a new lower maintenance clustering approach for minimizing the overhead of the network. As a result, the proposed approach showed a better result in the average end-to-end delay, packet delivery ratio, routing load, and throughput.