Improvement in packet-reordering with limited re-sequencing buffers: An analysis

Narasiodeyar, Raghunandan Mandyam; Jayasumana, Anura P.

doi:10.1109/lcn.2013.6761274

Cited by 8 publications

(3 citation statements)

References 19 publications

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“…Metrics such as Reordering Density (RD) have demonstrated effective performance and have been validated in several studies [35,93,94]. Other metrics, such as Reordering Buffer Density (RBD), have found applications in a variety of contexts [95][96][97][98][99][100][101]. Figure 9 summarizes these advanced metrics, with symbols indicating satisfaction level.…”

Section: Advanced Metricsmentioning

confidence: 99%

Packet Reordering in the Era of 6G: Techniques, Challenges, and Applications

Lin¹,

Zhang²,

Gao³

et al. 2023

Electronics

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The advent of sixth-generation (6G) networks brings unmatched speed, reliability, and capacity for massive connections, making it a cornerstone for revolutionary applications. One such application is in vehicular networks, which have their unique demands and complexities. Specifically, they face the complex issue of packet reordering due to the high-speed movement of vehicles and frequent switching of network connections. This paper examines the impact and causes of packet reordering, its threats to network efficiency, and potential countermeasures, particularly in the context of 6G-enabled vehicular networks. We introduce end-to-end methods and metrics to address packet reordering in 6G, discussing the development trends and application prospects. Our findings highlight the emergence of sophisticated strategies, such as prediction and avoidance, to manage packet reordering. They also reveal potential applications to boost network reliability, emulate traffic distributions, and enhance data security. Furthermore, we anticipate a growing integration of machine learning and data-driven optimization in tackling packet reordering. The insights provided aim to influence the future design and optimization of 6G networks, particularly concerning packet management and performance. This paper aims to assist researchers and practitioners in effectively leveraging packet reordering to promote efficient and secure operations of future 6G networks.

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Section: Advanced Metricsmentioning

confidence: 99%

Packet Reordering in the Era of 6G: Techniques, Challenges, and Applications

Lin¹,

Zhang²,

Gao³

et al. 2023

Electronics

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“…When sender discovers that data has been lost in the network, it retransmits the missing packets to recover the data, which further causes retransmission overhead problem. Recovering from losses can be done either applying timer-driven retransmission or data-driven retransmission [3] [6]. In Timedriven recovery, if a sender does not receive a positive cumulative ACK for a packet within a certain time-out interval, it retransmits the missing data.…”

Section: )mentioning

confidence: 99%

Reliable delay sensitive loss recovery protocol for critical health data transmission system

Kathuria

Gambhir

2015

2015 International Conference on Futuristic Trends on Computational Analysis and Knowledge Management (ABLAZE)

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Wireless Body Area Network (WBAN) is a special kind of sensor network deployed with low power, intelligent sensors, which are placed on the human body to collect human's vital signs, while monitoring body functions and the surrounding environment. Many applications of WBAN demand Reliable communication service; since the majority of these applications are responsible for handling time-critical data. Such an application area is a healthcare system, which offers flexibility and mobility to patients through the internet. Due to the long propagation delay and high loss rate in the WBAN, it is very tough to provide reliable data transfer for time-critical applications. In this paper, we analyze all these issues and design an efficient Reliable Delay Sensitive Loss Recovery protocol (RDSLR) for handling critical and non-critical data in WBAN. We emphasize on arrival of heterogeneous data (i.e. traffic flow) within the expected time for the analysis of actual health conditions of a patient. Reliable and loss-free data transmission requirements in a healthcare system desire arrival of data within the predefined critical time interval. Thereby, we enhance the loss recovery and delay module considering critical time parameters as an account. We evaluate the performance of the proposed approach by taking packet loss rate, elapse time, loss error time, and reliability time as key metrics.

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“…The reordering of network packets has been described formally and the impact of re-sequencing on the performance of streaming applications has been evaluated [18]. Two metrics are considered: reordering density, defining the distribution of the displacement of packets from their original position, and reordering buffer occupancy density which is the degree of occupancy of a buffer used for re-sequencing out-of-order packets.…”

Section: Related Workmentioning

confidence: 99%

Cardinality of UDP Transmission Outcomes

Weitl

Sebih

Artho³

et al. 2015

Dependable Software Engineering: Theories, Tools, and Applications

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Abstract. This paper examines the cost of testing network applications using the User Datagram Protocol (UDP). Such applications must deal with packet loss, duplication, and reordering. Ideally, a UDP application should be tested against all possible outcomes of unreliable UDP transmissions. Their number, however, grows at least exponentially in the number of transmitted packets. To estimate the cost of the exhaustive testing of UDP applications, we determine the number of UDP transmission outcomes analytically. Based on this combinatorial analysis, we derive a sound, complete, and optimal algorithm for generating outcomes of unreliable UDP transmissions. The algorithm is implemented in the net-iocache extension of the software model checker Java Pathfinder (JPF). Experimental results confirm the consistency of the implementation with the analytical results. In addition, we found that JPF's state matching reduces the explored state space significantly and ensures the practicability of the approach despite of its exponential complexity.

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Improvement in packet-reordering with limited re-sequencing buffers: An analysis

Cited by 8 publications

References 19 publications

Packet Reordering in the Era of 6G: Techniques, Challenges, and Applications

Packet Reordering in the Era of 6G: Techniques, Challenges, and Applications

Reliable delay sensitive loss recovery protocol for critical health data transmission system

Cardinality of UDP Transmission Outcomes

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