Buffer Management Scheme Research Articles

Buffer with N Policy and Active Management

The N policy is a buffer and transmission management scheme proposed for nodes in wireless sensor networks to save energy. It exploits the concept that the output radio of a node is initially switched off until a critical queue of packets is built up. Then, the output transmission begins and continues until the buffer is completely flushed. The cycle then repeats. In this study, we analyze a buffer with the N policy, equipped additionally with active queue management, which allows for dropping some packets depending on the current buffer occupancy. This extension enables controlling the performance of the node to a much greater extent than in the original N policy. The main contribution is the formulae for the key performance characteristics of the extended policy: the queue size distribution, throughput, and energy efficiency. These formulae are proven for a model with a general distribution of service time and general parameterizations of active management during the energy-saving and transmission phases. Theoretical results are followed by sample numerical calculations, demonstrating how the system’s performance can be controlled using active management in the transmission phase, the energy-saving phase, or both combined. The influence of the threshold value in an actively managed buffer is then shown and compared with its passive counterpart. Finally, solutions to some optimization problems, with the cost function based on the trade-off between the queue length and throughput, are presented.

Gem5-NVDLA: A Simulation Framework for Compiling, Scheduling and Architecture Evaluation on AI System-on-Chips

Recent years have seen an increasing trend in designing AI accelerators together with the rest of the system, including CPUs and memory hierarchy. This trend calls for high-quality simulators or analytical models that enable such kind of co-exploration. Currently, the majority of such exploration is supported by AI accelerator analytical models. But such models usually overlook the non-trivial impact of congestion of shared resources, non-ideal hardware utilization and non-zero CPU scheduler overhead, which could only be modeled by cycle-level simulators. However, most simulators with full-stack toolchains are proprietary to corporations, and the few open-source simulators are suffering from either weak compilers or limited space of modeling. This framework resolves these issues by proposing a compilation and simulation flow to run arbitrary Caffe neural network models on the NVIDIA Deep Learning Accelerator (NVDLA) with gem5, a cycle-level simulator, and by adding more building blocks including scratchpad allocation, multi-accelerator scheduling, tensor-level prefetching mechanisms and a DMA-aided embedded buffer to map workload to multiple NVDLAs. The proposed framework has been tested and verified on a set of convolution neural networks, showcasing the capability of modeling complex buffer management strategies, scheduling policies and hardware architectures. As a case study of this framework, we demonstrate the importance of adopting different buffering strategies for activation and weight tensors in AI accelerators to acquire remarkable speedup.

Firefly Optimization-Based Buffer Replacement Algorithm to Improve Nand Flash Memory Performance

Because of its shock tolerance, nonvolatility, low power consumption, and fast I/O speed, flash memory is often used for storage in consumer applications and, more recently, in the business computer environment. State drives SSDs to have not-in-place updates and asymmetric I/O latency, with write/erase operations being substantially slower than read operations. In this paper, we propose a buffer replacement technique FBRA that uses the firefly algorithm (FA) to precisely predict whether the pages residing in the buffer is hot or cold. The firefly optimization estimates hot fitness value of each page in the buffer in order to accurately classify them as hot or cold by characterizing precisely the temporal and spatial locality. To increase the hit ratio and SSD buffer use, the frequently used pages should stay longer in buffer compared to other pages. The proposed approach outperforms the existing SSD buffer management strategies regarding buffer hit ratio, write count, and runtime. Trace-driven simulation is done using FlashDB Simulator to support the performance of our approach surpasses various traditional buffer replacement policies.

Firefly Optimization-Based Buffer Replacement Algorithm to Improve Nand Flash Memory Performance

Because of its shock tolerance, nonvolatility, low power consumption, and fast I/O speed, flash memory is often used for storage in consumer applications and, more recently, in the business computer environment. State drives SSDs to have not-in-place updates and asymmetric I/O latency, with write/erase operations being substantially slower than read operations. In this paper, we propose a buffer replacement technique FBRA that uses the firefly algorithm (FA) to precisely predict whether the pages residing in the buffer is hot or cold. The firefly optimization estimates hot fitness value of each page in the buffer in order to accurately classify them as hot or cold by characterizing precisely the temporal and spatial locality. To increase the hit ratio and SSD buffer use, the frequently used pages should stay longer in buffer compared to other pages. The proposed approach outperforms the existing SSD buffer management strategies regarding buffer hit ratio, write count, and runtime. Trace-driven simulation is done using FlashDB Simulator to support the performance of our approach surpasses various traditional buffer replacement policies.

Physical and Data Link Layer Performance Enhancement in MANET to Overcome Hidden -Exposed Node Problem and Packet Loss Due to Buffer Overflow

In order to improve the performance of the MANET , the lower layers of MANET protocol stack has to improve the performance to overcome the hidden and expose node problem in the Physical layer and better buffer management scheme to be included in the data link layer .MAC layer in MANET ,Some cases the transmission range of the node can be idle but due to Hidden and Exposed node , the node could not be send the packet to other nodes. Node has to wait unnecessarily event the transmission medium is free. In case of more traffic in the MANET can leads to overflow in the buffer which causes the packet loss in the transmission. If any packet missed on the transmission the source node has to retransmit to the destination. This research article proposed the Mutual Exclusion MAC protocol for avoiding hidden and exposed terminal problem in MANET and active buffer management algorithm named Intelligent better buffer management (IBM) algorithm which improves the MANET nodes buffers to avoid packet loss . The proposed protocol is implemented with the support of Network simulator 3 and results are compared with the existing different protocol proposed for the MAC layer with the parameter and buffer management schemes and results shown the enhanced results shown.

Continual Unsupervised Domain Adaptation in Data-Constrained Environments

Domain Adaptation (DA) techniques aim to overcome the domain shift between the source domain used for training and the target domain where testing takes place. However, current DA methods assume that the entire target domain is available during adaptation, which may not hold in practice. We introduce a new, data-constrained DA paradigm where unlabeled target samples are received in batches and adaptation is performed continually. We propose a novel source-free method for continual unsupervised domain adaptation that utilizes a buffer for selective replay of previously seen samples. In our continual DA framework, we selectively mix samples from incoming batches with data stored in a buffer using buffer management strategies and use the combination to incrementally update our model. We evaluate and compare the classification performance of the continual DA approach with state-of-the-art (SOTA) DA methods based on the entire target domain. Our results on three popular DA datasets demonstrate the benefits of our method when operating in data constrained environments. We further extend our experiments to adapting over multiple target domains and our method performs favorably with the SOTA methods.

Range aware message drop policy for delay tolerant networks.

In delay tolerant networks (DTNs) the messages are often not delivered to the destination due to a lack of end-to-end connectivity. In such cases, the messages are stored in the buffer for a long time and are transmitted when the nodes come into the range of each other. The buffer size of each node has a limited capacity, and it cannot accommodate the new incoming message when the buffer memory is full, and as a result network congestion occurs. This leads to a low delivery probability and thus increases the overhead ratio. In this research work, a new buffer management scheme called Range Aware Drop (RAD) is proposed which considers metrics such as message size and time to live (TTL). RAD utilizes TTL as an important metric and as a result, reduces the unnecessary message drop. Simulation results reveal that RAD performs significantly better than drop oldest (DOA) and size aware drop (SAD) in terms of delivery probability and overhead ratio. The obtained results also revealed that the hop-count average of SAD is 3.9 and DOA is 3.4 while the hop-count average of RAD is just 1.7. Also, the message drop ratio of the RAD is 36.2% while SAD and DOA have message drop ratios of 73.3% and 84.9% respectively.

Buffer Management Techniques in Delay Tolerant Networks: A Comprehensive Survey

Abstract: This paper aims to provide a comprehensive study of the underlying buffer management issues and challenges in developing an efficient DTN routing protocol. Our aim is to begin with the discussion of buffer management schemes in DTNs in full generality and then dive in-depth, covering aspects of buffer management. Buffer strategies are used to determine which packets need to be forwarded or dropped. This paper will focus on the variety of buffer management strategies available, providing a comprehensive survey and analysis. We have also conducted an empirical analysis using simulator ONE to analyze the buffering time in various primary routing protocols such as Epidemic, Spary-and-wait (SNW), Prophet, Encounter based Routing (EBR) and Inter-Contact Delay and Location Information based Routing (ICDLIR). For these algorithms, it is also observed how varying the buffer size effect the delivery probability and overhead.

Evaluation of the Impact of Buffer Management Strategies on Biopharmaceutical Manufacturing Process Mass Intensity

There is an increasing demand to improve the overall sustainability of the biopharmaceutical industry. A barrier to improvement has been the limited research undertaken in the area of environmental impact of key design decisions. The aim of this study was to perform a comprehensive evaluation of the impact of buffer management strategy and technology selection on overall process efficiency using process mass intensity (PMI) as a metric for comparison. The environmental impact of buffer management has yet to be fully understood, despite buffers being one of the most resource-intensive aspects of biopharmaceutical manufacturing. A detailed process model was used to evaluate the impact of buffer management on a monoclonal antibody (MAB) process at the 2000 L scale. This was achieved by means of a non-replicated full factorial design composed of six variables: product titre, quantity of unique buffers, preparation frequency, single-use threshold and equipment cleaning duration with two levels and buffer preparation strategy type with four levels. The study identified that buffer management has a critical impact on overall process mass intensity, demonstrating a possibility to achieve a reduction in PMI of up to 90% for the best scenario compared to the worst. The findings also indicated that single-use systems are greatly superior to stainless-steel systems in terms of overall process efficiency, which is consistent with established thinking. The results from this research represent a further significant step towards achieving a more sustainable biopharmaceutical industry, establishing buffer management as a critical focus area, quantifying the influence of key variables on process mass intensity and highlighting the benefits of using a process mass intensity metric as part of routine biopharmaceutical design.

Cooperative Buffer Management With Fine-Grained Data Migrations for Hybrid Memory Systems

Hybrid memory composed of DRAM and persistent memory (PM) offers a promising way to realize large-capacity main memory supporting in-memory data storage and computing. However, traditional buffer management schemes focus on improving the hit ratio but lack awareness of the limitations of PM, e.g., slower write time and lower write endurance than DRAM. Therefore, developing new buffer management policies that can reduce costly write-backs of PM blocks while maintaining high performance for the hybrid buffer, is of paramount importance. Existing approaches mainly use a page-grained buffering policy, which will cause unnecessary data migrations between DRAM and PM, leading to a high number of disk I/Os and PM writes. Aiming to reduce I/O costs and PM writes, we propose a new buffer manager named HiBuffer for DRAM/PM-based hybrid memory systems. HiBuffer presents several novel ideas. First, it adopts multi-grained data layouts to manage the hybrid buffer cooperatively. In addition to the page granularity, we introduce Lines for the DRAM buffer and Sectors to the PM buffer, forming a buffer with three granularities, including Line, Sector, and Page. We prove that the multi-grained cooperative buffer management can deliver higher performance than existing page-grained schemes. Second, we propose a sector-grained method to migrate data from DRAM to PM, which can avoid unnecessary data movements and reduce PM writes. Third, we use an out-of-place updating mechanism to absorb updates in DRAM, which can further reduce the writes to PM. We compare HiBuffer with three existing schemes, including LRU, CLOCK-DWF, and MiniPage, on five synthetic workloads and the YCSB benchmark using real Intel Optane DC Persistent Memory. The results in terms of various metrics, including running time, PM writes, hit ratio, and disk I/Os, suggest the efficiency of HiBuffer. In particular, HiBuffer reduces the running time by up to 37.8% and the writes to PM by up to 83% compared to the competitors when evaluated on the YCSB benchmark.

MCB: a multidevice cooperative buffer management strategy for boosting the write performance of the SSD-SMR hybrid storage

MCB: a multidevice cooperative buffer management strategy for boosting the write performance of the SSD-SMR hybrid storage

Non-Stationary Characteristics of AQM Based on the Queue Length.

We performed a non-stationary analysis of a class of buffer management schemes for TCP/IP networks, in which the arriving packets were rejected randomly, with probability depending on the queue length. In particular, we derived formulas for the packet waiting time (queuing delay) and the intensity of packet losses as functions of time. These results allow us to observe how the evolution of the waiting time and losses depend on initial conditions (e.g., the full buffer) and system parameters (e.g., dropping probabilities, load, packet size distribution). As side results, the stationary waiting time and packet loss probability were obtained. Numerical examples demonstrate applicability of the theoretical results.

Efficient Multimedia Content Transmission Model for Disaster Management using Delay Tolerant Mobile Adhoc Networks

Natural and manmade disasters such as earthquakes, floods, unprecedented rainfall, etc. pose several threats to our society. The citizens upload disaster information in the form of multimedia content such as pictures, audio, and videos. Efficient information and communication framework are critical for disaster management. Mobile Adhoc Networks (MANET) have been used effectively for disaster management. However, Disaster management prerequisites following Quality of Service (QoS) requirements such as bandwidth, high delivery ratio, low overhead, and minimal latency; however, the existing data transmission scheme induces high latency and overhead among intermediate devices; In order to meet the QoS requirement of disaster management applications in this paper, High Delivery Efficiency and Low Latency Multimedia Content Transmission (HDELL-MCT) scheme for MANETs is presented. Then, an improved buffer management scheme is presented for meeting disaster management performance and latency prerequisites. The experiment is conducted using ONE Simulator, the outcome shows the HDELL-MCT scheme achieves very good performance considering different QoS metrics such as improving delivery ratio by 38.02%, reducing latency by 7.53% and minimizing hop communication overhead by 65.1% in comparison with existing multimedia content transmission model.

Semantic Metrics for Non Real-Time Applications

In this work, we investigate the issue of semantics in non real-time communication scenarios, that is, without stringent information delivery constraints. While semantics has been widely used in the context of communications, the definition of the semantic metrics has been limited to the real-time applications. We thus revise the basic concepts of the timeliness and the accuracy and propose their formal definitions in the case of non real-time applications characterized by a possibility of non-causal signal reconstruction at the destination. In particular, we link the concept of accuracy to the canonical first-order auto-regressive model of the signal, while the timeliness is defined by the time difference to reference samples of the signal. We compare the proposed semantic metrics in the case of different buffer management strategies and using numerical examples we show that the optimality of the transmission strategy changes when the real-time or non real-time applications are considered.

URM: A Unified RAM Management Scheme for NAND Flash Storage Devices

In NAND flash storage devices, the random access memory (RAM) is composed of a data buffer and mapping cache that play critical roles in storage performance. Furthermore, as the capacity growth rate of RAM chips lags far behind that of flash memory chips, determining how to take advantage of precious RAM is still a crucial issue. However, most existing buffer management studies on storage devices report performance degradation since these devices cannot refine reference regularities such as sequential, hot, or looping data patterns. In addition, most of these studies focus only on separately managing the data buffer or mapping cache. Compared with the existing buffer/cache management schemes (BMSs), we propose a unified RAM management (URM) scheme for not only the mapping cache but also the data buffer in NAND flash storage devices. URM compresses the mapping table to save memory space, and the remaining dynamic RAM space is used for the data buffer. For the data buffer part, we utilize the program counter‐technique in the host layer that provides automatic pattern recognition for different applications, in contrast to existing BMSs. The program counter‐technique in our design is able to distinguish four patterns. According to these patterns, the data buffer is divided into four size‐adjustable zones. Therefore, our approach is linked to multimodal data and used in a data‐intensive system. In particular, in URM, we use a multivariate classification to predict prefetching length in mapping buffer management. Our multivariate classification is transformed into multiple binary classifications (logistic regressions). Finally, we extensively evaluate URM using various realistic workloads, and the experimental results show that, compared with three data buffer management schemes, CFLRU, BPLRU, and VBBMS, URM can improve the hit ratio of data buffer and save response time by an average to 32% and 18%, respectively.

AOIO: Application Oriented I/O Optimization for Buffer Management

Emerging scale-out I/O intensive applications are broadly used now, which process a large amount of data in buffer/cache for reorganization or analysis and their performances are greatly affected by the speed of the I/O system. Efficient management scheme of the limited kernel buffer plays a key role in improving I/O system performance, such as caching hinted data for reuse in future, prefetching hinted data, and expelling data not to be accessed again from a buffer, which are called proactive mechanisms in buffer management. However, most of the existing buffer management schemes cannot identify data reference regularities (i.e., sequential or looping patterns) that can benefit proactive mechanisms, and they also cannot perform in the application level for managing specified applications. In this paper, we present an A pplication Oriented I/O Optimization (AOIO) technique automatically benefiting the kernel buffer/cache by exploring the I/O regularities of applications based on program counter technique. In our design, the input/output data and the looping pattern are in strict symmetry. According to AOIO, each application can provide more appropriate predictions to operating system which achieve significantly better accuracy than other buffer management schemes. The trace-driven simulation experiment results show that the hit ratios are improved by an average of 25.9% and the execution times are reduced by as much as 20.2% compared to other schemes for the workloads we used.

SS‐Drop: A Novel Message Drop Policy to Enhance Buffer Management in Delay Tolerant Networks

A challenged network is one where traditional hypotheses such as reduced data transfer error rates, end‐to‐end connectivity, or short transmissions have not gained much significance. A wide range of application scenarios are associated with such networks. Delay tolerant networking (DTN) is an approach that pursues to report the problems which reduce communication in disrupted networks. DTN works on store‐carry and forward mechanism in such a way that a message may be stored by a node for a comparatively large amount of time and carry it until a proper forwarding opportunity appears. To store a message for long delays, a proper buffer management scheme is required to select a message for dropping upon buffer overflow. Every time dropping messages lead towards the wastage of valuable resources which the message has already consumed. The proposed solution is a size‐based policy which determines an inception size for the selection of message for deletion as buffer becomes overflow. The basic theme behind this scheme is that by determining the exact buffer space requirement, one can easily select a message of an appropriate size to be discarded. By doing so, it can overcome unnecessary message drop and ignores biasness just before selection of specific sized message. The proposed scheme Spontaneous Size Drop (SS‐Drop) implies a simple but intelligent mechanism to determine the inception size to drop a message upon overflow of the buffer. After simulation in ONE (Opportunistic Network Environment) simulator, the SS‐Drop outperforms the opponent drop policies in terms of high delivery ratio by giving 66.3% delivery probability value and minimizes the overhead ratio up to 41.25%. SS‐Drop also showed a prominent reduction in dropping of messages and buffer time average.

Memory-Side Prefetching Scheme Incorporating Dynamic Page Mode in 3D-Stacked DRAM

Modern multiprocessor systems running multiple applications concurrently exhibit irregular memory access pattern during different phases of execution. The principle of locality is hard to exploit in the presence of such irregular memory requests and may result in additional delays due to resource conflicts throughout memory hierarchy. Prefetching is a promising technique to reduce the memory access latency where data is speculatively fetched ahead of time and stored in a faster memory structure like cache or dedicated prefetch buffer. The emergence of 3D-stacked DRAM provides huge internal bandwidth that makes memory-side prefetching an effective approach to improving system performance. Leveraging the unique architecture of 3D-stacked DRAM, we introduce a memory-side prefetching scheme that works in conjunction with dynamic page mode to reduce memory access latency. We introduce a novel prefetch buffer management scheme that makes intelligent replacement decision based on the utilization and recency of the prefetched data, which also serves as a guidance for future prefetching. Simulation results indicate that our approach improves performance by 21.8 percent on average, compared to a baseline scheme that prefetches a whole row on consecutive hits and implements static open page policy. Our scheme also outperforms an existing memory-side prefetching scheme by 13.2 percent on average, which dynamically adjusts the prefetch degree based on the usefulness of prefetched data.

RESCUE: A Resilient and Secure Device-to-Device Communication Framework for Emergencies

During disasters, existing telecommunication infrastructures are often congested or even destroyed. In these situations, mobile devices can form a backup communication network for civilians and emergency services using disruption-tolerant networking (DTN) principles. Unfortunately, such distributed and resource-constrained networks are particularly susceptible to a wide range of attacks such as terrorists trying to cause more harm. In this article, we present <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">RESCUE</i> , a resilient and secure device-to-device communication framework for emergency scenarios that provides comprehensive protection against common attacks. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">RESCUE</i> features a minimalistic DTN protocol that, by design, is secure against notable attacks such as routing manipulations, dropping, message manipulations, blackholing, or impersonation. To further protect against message flooding and Sybil attacks, we present a twofold mitigation technique. First, a mobile and distributed certificate infrastructure particularly tailored to the emergency use case hinders the adversarial use of multiple identities. Second, a message buffer management scheme significantly increases resilience against flooding attacks, even if they originate from multiple identities, without introducing additional overhead. Finally, we demonstrate the effectiveness of <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">RESCUE</i> via large-scale simulations in a synthetic as well as a realistic natural disaster scenario. Our simulation results show that <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">RESCUE</i> achieves very good message delivery rates, even under flooding and Sybil attacks.

RESCUE: A Resilient and Secure Device-to-Device Communication Framework for Emergencies

During disasters, existing telecommunication infrastructures are often congested or even destroyed. In these situations, mobile devices can form a backup communication network for civilians and emergency services using disruption-tolerant networking (DTN) principles. Unfortunately, such distributed and resource-constrained networks are particularly susceptible to a wide range of attacks such as terrorists trying to cause more harm. In this paper, we present RESCUE, a resilient and secure device-to-device communication framework for emergency scenarios that provides comprehensive protection against common attacks. RESCUE features a minimalistic DTN protocol that, by design, is secure against notable attacks such as routing manipulations, dropping, message manipulations, blackholing, or impersonation. To further protect against message flooding and Sybil attacks, we present a twofold mitigation technique. First, a mobile and distributed certificate infrastructure particularly tailored to the emergency use case hinders the adversarial use of multiple identities. Second, a message buffer management scheme significantly increases resilience against flooding attacks, even if they originate from multiple identities, without introducing additional overhead. Finally, we demonstrate the effectiveness of RESCUE via large-scale simulations in a synthetic as well as a realistic natural disaster scenario. Our simulation results show that RESCUE achieves very good message delivery rates, even under flooding and Sybil attacks.