A novel scheduling algorithm for input-queued switches

The delay and throughput characteristics of a packet switch depend mainly on the queueing scheme and the scheduling algorithm deployed at the switch. Early research on scheduling algorithms has mainly focused on maximum weight matching scheduling algorithms. It is known that maximum weight matching algorithms guarantee the stability of input-queued switches, but are impractical due to their high computational complexity. Later research showed that the less complex maximal matching algorithms can stabilize input-queued switches when they are deployed with a speed-up of two. For practical purposes, neither a high computational complexity nor a speed-up of two is desirable.In this paper, we investigate the application of matching algorithms that approximate maximum weight matching algorithms to scheduling problems. We show that while having a low computational complexity, they guarantee the stability of input queued switches when they are deployed with a moderate speed-up.In particular, we show that the improve_matching algorithm stabilizes input-queued switches when it is deployed with a speed-up of 3<over>2+ε.In a second step, we further improve on these results by proposing a class of maximal weight matching algorithms that stabilize an input-queued switch without any speed-up.Whereas initial research has only focused on scheduling algorithms that guarantee the stability of a single switch, recent work has shown how scheduling algorithms for single switches can be modified in order to design distributed scheduling algorithms that stabilize networks of input-queued switches. Using those results, we show that the switching algorithms proposed in this paper do not only stabilize a single switch, but also networks of input-queued switches.

Input-Queued switching fabrics are widely used in high speed network switches for their scalability. However, a scheduling algorithm must be elaborative designed for input-queued switches to get high throughput. The randomized algorithms are attractive in kinds of scheduling algorithms for their low complexity and well performance. In this paper, a fluid model is introduced to analyze the rate stability of switching systems with randomized schedulers. By this method, we proved that the randomized scheduling algorithm can achieve 100% throughput under any admissible traffics which satisfy the strong law of large numbers (SLLN).

In this paper, we present the performance analysis of the 32×32 crosspoint queued (CQ) switch. The CQ switch architecture has been recently brought back into focus since modern technology enables an easy implementation of large buffers in crosspoints. An advantage of this solution is the absence of credit based control communication between linecards and schedulers. In this paper, the performances of four algorithms (longest queue first, round robin, exhaustive round robin and frame based round robin matching), are analyzed and compared. The results obtained for the CQ switch are compared with the output queued switch. Throughput, average cell latency and instantaneous packet delay variance are evaluated under uniform and nonuniform traffic patterns. Also, original iterative method for CQ switch throughput calculation under the uniform traffic is presented. The results will show that the longest queue first algorithm has the highest throughput in many simulated cases, but the highest average cell latency and delay variance among observed algorithms. It will also be shown that the choice of the scheduling algorithm does not play a role in the switch performance if the buffers are long enough. This will prove that some form of round robin based algorithms become a better choice for implementation due to their simplicity, small hardware requirements and avoidance of the starvation problem, which is a major drawback of the longest queue first algorithm. The proposed iterative method for throughput calculation gives results very close to the results obtained by numerous simulations, especially for larger switch and long buffers.

Scheduling algorithms for input-queued packet switches have been widely researched. It has been shown that various classes of scheduling algorithms provide guarantees on stability and on average delay for single switches. However, recent research has demonstrated that most of these scheduling algorithms do not guarantee stability for networks of switches. Most of the research that treats networks of switches proposes switching policies that require coordination among the single switches. The problem to find <i>distributed</i> scheduling policies that guarantee the stability of a network of switches has so far only been investigated for a policy based on a computationally very complex maximum weight matching algorithm. In this paper, we investigate <i>distributed</i> scheduling algorithms of <i>low complexity</i> that belong to the classes of maximal weight matching algorithms, <i>p</i>-maximal weight matching algorithms for switch architectures based on a space-division multiplexing extension, and MNCM algorithms. For these scheduling algorithms, we prove the stability of networks of input-queued switches where all switches deploy the same scheduling policy. We also show that networks of input-queued switches in which specific classes of different switching policies are deployed simultaneously at different switches are stable.

The 5G user plane function (UPF) is a critical inter-connection point between the data network and cellular network infrastructure. It governs the packet processing performance of the 5G core network. UPFs also need to be flexible to support several key control plane operations. Existing UPFs typically run on general-purpose CPUs, but have limited performance because of the overheads of host-based forwarding. We design Synergy, a novel 5G UPF running on SmartNICs that provides high throughput and low latency. It also supports monitoring functionality to gather critical data on user sessions for the prediction and optimization of handovers during user mobility. The SmartNIC UPF efficiently buffers data packets during handover and paging events by using a two-level flow-state access mechanism. This enables maintaining flow-state for a very large number of flows, thus providing very low latency for control and data planes and high throughput packet forwarding. Mobility prediction can reduce the handover delay by pre-populating state in the UPF and other core NFs. Synergy performs handover predictions based on an existing recurrent neural network model. Synergy's mobility predictor helps us achieve 2.32× lower average handover latency. Buffering in the SmartNIC, rather than the host, during paging and handover events reduces packet loss rate by at least 2.04×. Compared to previous approaches to building programmable switch-based UPFs, Synergy speeds up control plane operations such as handovers because of the low P4-programming latency leveraging tight coupling between SmartNIC and host.

As the large amount of video surveillance data floods into cloud data center, achieving load balancing in a cloud network has become a challenging problem. Meanwhile, we hope the cloud data center maintains low latency, low consumption, and high throughput performance when transmitting massive amounts of data. OpenFlow enables a software-defined solution through programing to control the scheduling of data flow in the cloud data center. However, the existing scheduling algorithm of the data center cannot cope with the congestion of the network center effectively. Even for some dynamic scheduling algorithms, adjustments can only be made after congestion occurs. Hence, we propose a proactive and dynamically adjusted mixed-flow load-balanced scheduling (MFLBS) algorithm, which not only takes into account the different sizes of flows in the network but also maintains maximum throughput while balancing the load. In this paper, the MFLBS problem was formulated, along with a set of heuristic algorithms for real-time feedback and adjustment. Experiments with mesh and tree network models show that our MFLBS is significantly better than other dynamic scheduling algorithms, including one-hop DLBS and static scheduling algorithm FCFS. The MFLBS algorithm can effectively reduce the delay of small flows and average delay while maintaining high throughput.

Scheduling plays an important role in providing quality of service (QoS) support to multimedia communications in various kinds of wireless networks, including cellular networks, mobile ad hoc networks, and wireless sensor networks. The authors propose a scheduling algorithm at the medium access control (MAC) layer for multiple connections with diverse QoS requirements, where each connection employs adaptive modulation and coding (AMC) scheme at the physical (PHY) layer over wireless fading channels. Each connection is assigned a priority, which is updated dynamically based on its channel and service status; the connection with the highest priority is scheduled each time. The authors' scheduler provides diverse QoS guarantees, uses the wireless bandwidth efficiently, and enjoys flexibility, scalability, and low implementation complexity. Its performance is evaluated via simulations.

This paper presents a Constraint-Based Routing (CBR) algorithm for Multiprotocol Label Switching (MPLS) network which is designed for mapping among any layer-2 protocols and any layer-3 protocols of the OSI model. The MPLS network has capability of routing with some specific constraints for supporting desire Quality of Service (QoS). The most important constraint is the demand bandwidth. The efficient routing algorithm should have low percentage of call-setup request blocking, high network utilization and low calculation complexity. There are many previously proposed algorithms such as minimum hop algorithm, widest shortest path algorithm, and minimum interference routing algorithm. In this paper, a new algorithm is proposed. The proposed algorithm is based on the weight calculation of an amounts of paths routed over each links in the network. From the simulation results, the proposed algorithm has well performance over high network utilization, low blocking percentage and low complexity.

Cell-based input-queued crossbars are widely used in networking equipments. A number of crossbar scheduling algorithms have been proposed to provide high performance scheduling. It is critical for a crossbar scheduling algorithm to be fair and efficient in real world conditions, which include the presence of over-subscribed ingress ports and the possible flow control from the egress ports. Several commonly deployed algorithms are not fair when there are ingress congestions due to over-subscription. Furthermore, these algorithms lose fairness and can even cause starvation when there is flow control or backpressure from the egress ports. We illustrate the problems in detail using the well-known iSLIP algorithm. In this paper, we present a new algorithm, iSKIP, which performs as efficiently as iSLIP in a benign environment but remains fair and starvation-free in the cases of ingress congestion and egress backpressure. The iSKIP algorithm can be implemented in fast and simple hardware. Simulation results are presented to illustrate the advantages of the iSKIP algorithm.

Due to its fixed assignment nature, the well-known time division multiple access (TDMA) protocol suffers from poor performance when the offered traffic is bursty. In this paper, an adaptive TDMA protocol, which is capable of operating efficiently under bursty traffic conditions, is introduced. According to the proposed protocol, the station which is granted permission to transmit at each time slot is selected by means of learning automata (LA). The choice probability of the selected station is updated by taking into account the network feedback information. The system which consists of the LA and the network is analyzed and it is proven that the choice probability of each station asymptotically tends to be proportional to the probability that this station is not idle. Although there is no centralized control of the stations and the traffic characteristics are unknown and time-variable, each station tends to take a fraction of the bandwidth proportional to its needs. Furthermore, extensive simulation results are presented, which indicate that the proposed protocol achieves a significantly higher performance than other well-known TDMA protocols when operating under bursty traffic conditions.

In this paper, we propose a DDoS defense architecture, named NEIF (Network Egress and Ingress Filtering), which is deployed at the Internet Service Provider's (ISP) edge routers to prohibit DDoS attacks into and from the ISPs' networks. The main challenge is how to implement NEIF with a small fixed amount of memory and low implementation complexity so that it may be acceptable by ISPs. We first design a bloom filter based data structure to identify and measure a few relatively large flows instead of all flows, where the amount of required memory is independent of link speeds and the number of flows. Then, the relatively large flows are rate-limited to their fair share based on the packet symmetry-the ratio of received and transmitted packets of a host. The dropping decisions of each flow are made on the observed counters directly that are with low implementation complexity. Finally, we implement NEIF with Click and perform experiments on PlanetLab. The experimental results validate our analysis and show that the Internet can benefit from NEIF even under partial deployment.

A new fuzzy indirect adaptive controller for continuous-time nonlinear systems, with a poorly understood dynamics, is developed. The proposed adaptive scheme uses a single Takagi-Seguno (TS) fuzzy model with few parameters to learn, which results in low implementation complexity and a fast learning rate. In addition, the use of TS fuzzy model permits the inclusion of a priori knowledge about the plant dynamics in terms of exact mathematical models or qualitative information. Using the hyperstability approach, it is proved that this adaptive controller is globally asymptotically stable, and achieves asymptotic tracking of a stable reference model. The performance of the developed approach is illustrated with simulation results.

Robust codes ${\mathcal {C}}(n,k)_q$C(n,k)q are nonlinear $q$q-ary codes of dimension $k$k and length $n\leq 2k$n≤2k. Robust codes can detect any error with nonzero probability; hence, they can effectively detect fault injection attacks. Most high rate robust codes are either restricted to certain ratios between $n$n and $k$k, or have relatively high hardware complexity. This paper presents new constructions for optimum or close to optimum low complexity high rate robust codes. These codes exist for any $k$k and $n$n. The hardware complexity of each construction is discussed, and a method to choose the one with the smallest implementation cost is presented.

The achievable performance of channel coded space-time trellis (STT) codes and space-time block (STB) codes transmitted over wideband channels is studied in the context of schemes having an effective throughput of 2 bits/symbol (BPS) and 3 BPS. At high implementational complexities, the best performance was typically provided by Alamouti's unity-rate G/sub 2/ code in both the 2-BPS and 3-BPS scenarios. However, if a low complexity implementation is sought, the 3-BPS 8PSK space-time trellis code outperforms the G/sub 2/ code. The G/sub 2/ space-time block code is also combined with symbol-by-symbol adaptive orthogonal frequency division multiplex (AOFDM) modems and turbo convolutional channel codecs for enhancing the system's performance. It was concluded that upon exploiting the diversity effect of the G/sub 2/ space-time block code, the channel-induced fading effects are mitigated, and therefore, the benefits of adaptive modulation erode. In other words, once the time- and frequency-domain fades of the wideband channel have been counteracted by the diversity-aided G/sub 2/ code, the benefits of adaptive modulation erode, and hence, it is sufficient to employ fixed-mode modems. Therefore, the low-complexity approach of mitigating the effects of fading can be viewed as employing a single-transmitter, single-receiver-based AOFDM modem. By contrast, it is sufficient to employ fixed-mode OFDM modems when the added complexity of a two-transmitter G/sub 2/ scheme is affordable.

In this paper, we present a low-complexity low data rate (LDR) ultra wideband (UWB) transceiver prototype CMOS chip suitable for a differential binary phase shift keying (DBPSK) modulation applied data transmission with 500 MHz-bandwidth signals. This solution, which is mainly based on "1.5-bit" direct sub-sampling at 1 Gsps and differential digital correlations, enjoys good immunity to clock drift and interferers. It is also likely to offer an interesting trade-off between fine performance in dense multipath environments, low implementation complexity, and hence low power consumption. At first, the 1.5 bits concept is discussed. Then, the implementation choices for some critical blocks of the RX data path are discussed to justify the adopted low-complexity approach. Finally, some preliminary implementation results are provided.