Packet loss

About: Packet loss is a research topic. Over the lifetime, 21235 publications have been published within this topic receiving 302453 citations.

Method and system for identifying reasons of ZigBee sensor network packet loss

Abstract: The invention discloses a method and system for identifying reasons of ZigBee sensor network packet loss The method includes the steps that a receiving node carries out high-frequency sampling on corresponding receiving signal strength information and link quality information while receiving a data package; if the received data package fails to pass the cyclic redundancy check, collision mode fragments possibly existing in the high-frequency sampled receiving signal strength information and the high-frequency sampled link quality information are searched, and the modes monitored in the receiving signal strength information and the link quality information will be regrouped into a time-ordered mode sequence; the receiving node searches for the generated mode sequence and outputs the packet loss reasons of the damaged data package by using corresponding identifying rules; the receiving node adds the specific reasons of data package loss in an acknowledgment packet sent to a sending node Through the method, network throughput can be improved and retransmission frequency can be reduced, so the purposes of saving energy and prolonging working time can be achieved

Apparatus and method for providing quality of service for mixed traffic in a wireless network base station

Abstract: An apparatus and method for providing quality of service for the transmission of data packets from a base station in a wireless network to a plurality of mobile stations in a coverage area of the wireless network. The apparatus comprises a packet discriminator for receiving data packets from user devices requesting to transmit data packets to the mobile stations. The packet discriminator determines whether each data packet is a real time application or a non-real time application. The apparatus also comprises a real time traffic packet processor for receiving first selected data packets for real time applications, and a non-real time traffic packet processor for receiving second selected data packets for non-real time applications.

Bluetooth adaptive frequency hopping and scheduling

Abstract: In this paper, we investigate the use of adaptive frequency hopping (AFH) techniques aimed at modifying the Bluetooth frequency hopping sequence in the presence of WLAN direct sequence spread spectrum devices. We examine the conditions such as the applications, topologies, and scenarios under which AFH techniques improve performance that is measured in terms of packet loss, TCP delay, and channel efficiency. We also compare the results obtained with AFH to others obtained using a scheduling technique that consist in delaying the transmission of a Bluetooth packet until the medium is "idle". Our results show that an obvious performance improvement with AFH is in terms of delay and throughput. AFH brings the delay down to the same level than when no interference is present. On the other hand, AFH is rather slow in responding to changes in the environment and the packet loss is more significant than with the scheduling. This is probably due to the limitations imposed by the communication overhead. The main difficulty for AFH is having to dynamically communicate the changes to all slaves in the piconet in order to keep the synchronization.

Towards 5G: A Reinforcement Learning-Based Scheduling Solution for Data Traffic Management

Abstract: Dominated by delay-sensitive and massive data applications, radio resource management in 5G access networks is expected to satisfy very stringent delay and packet loss requirements In this context, the packet scheduler plays a central role by allocating user data packets in the frequency domain at each predefined time interval Standard scheduling rules are known limited in satisfying higher quality of service (QoS) demands when facing unpredictable network conditions and dynamic traffic circumstances This paper proposes an innovative scheduling framework able to select different scheduling rules according to instantaneous scheduler states in order to minimize the packet delays and packet drop rates for strict QoS requirements applications To deal with real-time scheduling, the reinforcement learning (RL) principles are used to map the scheduling rules to each state and to learn when to apply each Additionally, neural networks are used as function approximation to cope with the RL complexity and very large representations of the scheduler state space Simulation results demonstrate that the proposed framework outperforms the conventional scheduling strategies in terms of delay and packet drop rate requirements

Performance Modeling and Analysis of Network Firewalls

Abstract: Network firewalls act as the first line of defense against unwanted and malicious traffic targeting Internet servers. Predicting the overall firewall performance is crucial to network security engineers and designers in assessing the effectiveness and resiliency of network firewalls against DDoS (Distributed Denial of Service) attacks as those commonly launched by today's Botnets. In this paper, we present an analytical queueing model based on the embedded Markov chain to study and analyze the performance of rule-based firewalls when subjected to normal traffic flows as well as DoS attack flows targeting different rule positions. We derive equations for key features and performance measures of engineering and design significance. These features and measures include throughput, packet loss, packet delay, and firewall's CPU utilization. In addition, we verify and validate our analytical model using simulation and real experimental measurements.