Source anonymity in fair scheduling: A case for the proportional method

In data communication when there are too many packets contending for the limited shared resources, such as the queue buffer in the router at bottleneck link, it may result in congestion. During congestion, large amount of packets experience delay or even be dropped due to the queue overflow. Severe congestion problems result in degradation of the throughput and large packet loss rate. In this paper, analysis of throughput and packet loss rate for different buffer sizes is presented; taking into account two popular queue management methods, Random Early Detection (RED) and Drop Tail, for different TCP and UDP streams coming to a common router buffer. The results indicate that the throughput and efficiency of TCP increases with increase in buffer size for RED. Moreover, UDP packet loss decreases with an increase in buffer size while the buffer size has no key impact on UDP packet delays. Simulation has been done by using Network Simulator (NS2-2.37) and the graphs are plotted using GNU plot.

Fair scheduling algorithms have been proposed to tackle the problem of bursty and location-dependent errors in wireless packet networks. Most of those algorithms ensure the fairness property and guarantee the QoS of all sessions in a large-scale cellular network such as GSM or GPRS. In this paper, we propose the Weighted-Sacrificing Fair Queueing (WSFQ) scheduling algorithm for small-area and device-limited wireless networks. WSFQ slows down the growth of queue length in limited-buffer devices, still maintains the properties of fairness, and guarantees the throughputs of the system. Moreover, WSFQ can easily adapt itself to various kinds of traffic load. We also implement a packet-based scheduling algorithm, the Packetized Weighted Sacrificing Fair Queueing (PWSFQ), to approach the WSFQ. WSFQ and PWSFQ are evaluated by comparing with other algorithms by mathematical analysis and simulations.

Although weighted fair queueing (WFQ) has been regarded as an ideal scheduling algorithm in terms of its combined delay bound and proportional fairness properties, its asymptotic time complexity increases linearly with the number of sessions serviced by the scheduler, thus limiting its use in high-speed networks. An algorithm that combines the delay and fairness bounds of WFQ with O(1) timestamp computations had remained elusive so far. In this paper we present two novel scheduling algorithms that have O(1) complexity for timestamp computations and provide the same bounds on end-to-end delay and buffer requirements as those of WFQ. The first algorithm, frame-based fair queueing (FFQ), uses a framing mechanism to periodically recalibrate a global variable tracking the progress of work in the system, limiting any short-term unfairness to within a frame period. The second algorithm, starting potential based fair queueing (SPFQ), performs the recalibration at packet boundaries, resulting in improved fairness while still maintaining the O(1) timestamp computations. Both algorithms are based on the general framework of rate-proportional servers (RPSs) introduced by Stiliadis and Varma (see ibid., vol.6, no.2, p.164-74, 1998). The algorithms may be used in both general packet networks with variable packet sizes and in asynchronous transfer mode (ATM) networks.

In wavelength division multiplexing (WDM) star networks, the construction of the transmission schedule is a key issue, which essentially affects the network performance. Up to now, classic scheduling techniques consider the nodes' requests in a sequential service order. However, these approaches are static and do not take into account the individual traffic pattern of each node. Owing to this major drawback, they suffer from low performance, especially when operating under asymmetric traffic. In this paper, a new class of scheduling algorithms for WDM star networks, which is based on the use of clustering techniques, is introduced. According to the proposed Clustering‐Based Scheduling Algorithm (CBSA), the network's nodes are organized into clusters, based on the number of their requests per channel. Then, their transmission priority is defined beginning from the nodes belonging to clusters with higher demands and ending to the nodes of clusters with fewer requests. The main objective of the proposed scheme is to minimize the length of the schedule by rearranging the nodes' service order. Furthermore, the proposed CBSA scheme adopts a prediction mechanism to minimize the computational complexity of the scheduling algorithm. Extensive simulation results are presented, which clearly indicate that the proposed approach leads to a significantly higher throughput‐delay performance when compared with conventional scheduling algorithms. We believe that the proposed clustering‐based approach can be the base of a new generation of high‐performance scheduling algorithms for WDM star networks. Copyright © 2008 John Wiley & Sons, Ltd.

For sensor networks deployed to monitor and report real events, event source anonymity is an attractive and critical security property, which unfortunately is also very difficult and expensive to achieve. This is not only because adversaries may attack against sensor source privacy through traffic analysis, but also because sensor networks are very limited in resources. As such, a practical trade-off between security and performance is desirable. In this article, for the first time we propose the notion of statistically strong source anonymity , under a challenging attack model where a global attacker is able to monitor the traffic in the entire network. We propose a scheme called FitProbRate , which realizes statistically strong source anonymity for sensor networks. We demonstrate the robustness of our scheme under various statistical tests that might be employed by the attacker to detect real events. Our analysis and simulation results show that our scheme, besides providing source anonymity, can significantly reduce real event reporting latency compared to two baseline schemes. However, the degree of source anonymity in the FitProbRate scheme might decrease as real message rate increases. We propose a dynamic mean scheme which has better performance under high real message rates. Simulation results show that the dynamic mean scheme is capable of increasing the attacker's false positive rate and decreasing the attacker's Bayesian detection rate significantly even under high-rate continuous real messages.

Analysis of temporal and throughput fair scheduling in multirate WLANs

Anonymous communication, where users communicate without revealing the identities of communicating parties or the paths of data flow is critical in data networks. On the Internet, Chaum mixes, intermediate nodes, or proxy servers, which use layered encryption and packet shuffling methods to hide source identities, are used to provide anonymity to network users. In this paper, an information theoretic framework is developed to study the maximum anonymity achievable by packet shuffling when the mixes are memory limited-in other words, they can store a finite number of packets. Using the Shannon entropy of the a posteriori distribution of packet sources from an eavesdropper's perspective as the measure of anonymity, the maximum achievable anonymity of a single mix with buffer size b (packets) serving two independent Poisson sources with equal arrival rates is shown to be log [2 cos (π/b+3)]. For a general multiuser b+3 system, the maximum anonymity as buffer size b → ∞ is shown to approach the entropy of the source arrival probabilities at a convergence rate no lesser than 1/b <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> . When the arrival probabilities of the general multiuser system can be expressed as a rational fraction k/2 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">n</sup> for some fixed n, this convergence rate is shown to be achievable. The anonymity analysis is extended to a general network of mixes connecting the sources to a common destination, where the source anonymity achievable on the destination link is shown to be lower bounded by a weighted sum of the anonymity achievable by each individual mix.

Scheduling algorithms in wavelength division multiplexing (WDM) single-hop networks aim at producing an effective schedule in order to improve the networks' performance. Apart from channel assignment, the message sequencing is an important issue that have to be addressed when designing media access control (MAC) protocols for WDM networks. Up until now, popular approaches have not extensively addressed the order in which the messages are scheduled even though the messages' service order can considerably contribute to the advance of network performance. This paper introduces a new approach to the design of message scheduling algorithms for WDM star networks, which is based on the use of clustering techniques. The proposed clustering oriented-earliest available time scheduling (CO-EATS) creates groups of nodes whose messages are destined to common nodes. The goal of the proposed CO-EATS scheme is to decrease the probability of scheduling messages to the same destination at successive order. The simulation results have shown that the proposed scheme improves channel utilization and as a result it leads to higher network throughput while it keeps mean packet delay at low levels in comparison with conventional scheduling algorithms.

Partitioning and global scheduling are two approaches for scheduling real-time tasks in multiprocessor environments. Partitioning is the more favored approach, although it is sub-optimal. This is mainly due to the fact that popular uniprocessor real-time scheduling algorithms, such as EDF and RM, can be applied to the partitioning approach with low scheduling overhead. In recent years, much research has been done on global real-time multiprocessor scheduling algorithms based on the concept of “proportionate fairness”. Proportionate fair (Pfair) scheduling [5],[6] is the only known optimal algorithm for scheduling real-time tasks on multiprocessor. However, frequent preemptions caused by the small quantum length for providing optimal scheduling in the Pfair scheduling make it impractical. Deadline Fair Scheduling (DFS) [1] based on Pfair scheduling tried to reduce preemption-related overhead by means of extending quantum length and sharing a quantum among tasks. But extending quantum length causes a mis-estimation problem for eligibility of tasks and a non-work-conserving problem. In this paper, we propose the Enhanced Deadline Fair Scheduling (E-DFS) algorithm to reduce preemption-related overhead. We show that E-DFS allows us to decrease quantum length by reducing overhead and save wasted CPU time that is caused by preemption-related overhead and miss-estimation of eligibility.

To efficiently realize the low-latency scheduling of ultra-reliable low-latency communications (URLLC) and enhanced mobile broadband (eMBB) services in Industrial Internet of Things (IIoT), we propose a lightweight and, low-latency proactive grant scheduling (LL-PGS) algorithm. In the proposed LL-PGS, a lightweight channel-queue prediction algorithm, and an adaptive two-tier scheduling priority adjustment module are organically integrated. Through the cooperation between above modules, the proposed LL-PGS facilitates the low-latency and on-demand physical resource blocks (PRBs) scheduling without extra state report and grant feedback. Extensive simulation results demonstrate that the proposed LL-PGS can significantly reduce the signaling overhead and uplink latency without sacrificing throughput. Compared with conventional scheduling algorithms including round robin (RR), proportional fair (PF), exponential proportional fair (EXP/PF), and modification of largest weighted delay first (M-LWDF), the proposed LL-PGS can increase the average uplink throughput for eMBB services by 12.42%, and reduce latency for URLLC services to 1ms.

An analytical method is derived to estimate the protocol data unit (PDU) frame loss probability as a function of buffer size when identical sources are multiplexed on a fast packet link. The generation of PDUs from each source is governed by an on-off source model, and upper and lower bounds on the frame loss probability are derived. The analysis takes into account the correlated nature of fast packet losses within a PDU due to buffer overflows. The required buffer size for a given frame loss probability is directly proportional to the expected PDU frame length, and the loss probability decreases exponentially with increasing buffer size. >

Intuition suggests that a finite buffer limits the effect of traffic auto-correlations on the queue length. We investigate the extent to which finite buffers can, therefore, be expected to mitigate the effects of long-range dependence (LRD). With traffic sequences generated by the fractional autoregressive integrated moving average (f-ARIMA) models for LRD, and by AR models for short range dependence (SRD), we investigate the traffic performance for a range of finite buffers, both for single and multiplexed streams. For design, the aim is to 'match' a given LRD auto-correlation function with a suitable SRD function whose performance provides, for a wide range of traffic intensities and buffer sizes, a conservative bound on the performance associated with the LRD function. The results suggest that by suitably 'dominating' an LRD auto-correlation function by an SRD function, one can obtain conservative performance bounds for a realistic range of traffic intensities and buffer sizes (delays). Also, in several cases, a 'cross-over' phenomenon is observed for cell-loss probabilities as the buffer size increases, i.e., the loss probabilities are smaller for LRD than for SRD for small buffers, with the converse true for large buffers. This suggests that finite buffers, can in some cases, counteract the effects of LRD in traffic arrivals, and thus enable conservative designs to be based on Markovian traffic models.

Recently, there has been a tremendous increase in mobile data usage with widespread proliferation of smartphone like devices and increasing popularity of video streaming services such as YouTube. This is already causing overloading of 3G cellular access networks. It is estimated that even the 4G LTE (Long Term Evolution) technology which has significantly higher spectral efficiency than 3G will also face overloading in near future. As a result, it has become important to find out ways and means of offloading the traffic from the LTE network. One possible solution is offloading it to Wi-Fi to gain extra capacity and improve overall network performance. In this paper we have considered an outdoor macro cell LTE Network being offloaded by a Wi-Fi network. We study the loading of LTE Network in different types of user and traffic distribution and investigate how offload to Wi-Fi APs can help in easing the congestion in LTE network and thereby lead to better per user throughputs and better quality of experience to end users using NS-3. Also, among the various scheduling algorithms that have been defined for efficient resource allocation in LTE, three schedulers have been considered: Round Robin (RR), Proportional Fair (PF) and Priority Set Scheduler (PSS) schedulers and their performance has been evaluated in the offloading scenario.

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These days, the problems of scheduling and security are increasingly pressing as a result of the rapidly growing number of implementations that are operated in operating systems. Process scheduling and scheduling security is the most effective methodology of operating a system which can improve and degrade the performance of the computer system. The performance of scheduling algorithm in operating system can be measured by scheduling principles like average waiting time, average turnaround time, response time, throughput etc. Much research carried out over operating system security and round robin scheduling used in time sharing operating system in previous years to resolve the issues regarding to improvement in the performance of round robin (RR) scheduling and improving the security in the scheduling approach. This study discussed the security issues in operating systems, scheduling security and discrete structure of a new approach for RR scheduling. The researcher has suggested a list of policy for scheduling method security and proposed a new approach for RR scheduling and investigated the scheduling principles. The proposed methodology covers distinctive strategy for selection manner of process from ready queue than RR and used diverges time quantum. The proposed methodology has been validated experimentally by comparing with a numerous scheduling algorithm namely as Round Robin (RR), Adaptive Round Robin (ARR), Round Robin Remaining time (RRRT), improved Round Robin (IRR), an additional improvement on the improved Round Robin (AAAIRR), and an Enhanced Round Robin (ERR). Numerous simulations have been conducted to validate the effectiveness of the proposed algorithm to compelling the performance of system. At the conclusion the performance of computing system is dependent on security of operating system as well as secluding methods.