6,188 research outputs found
Incorporating TSN/BLS in AFDX for Mixed-Criticality Avionics Applications: Specification and Analysis
In this paper, we propose an extension of the AFDX standard, incorporating a
TSN/BLS shaper, to homogenize the avionics communication architecture, and
enable the interconnection of different avionics domains with mixed-criticality
levels, e.g., legacy AFDX traffic, Flight Control and In-Flight Entertainment.
First, we present the main specifications of such a proposed solution. Then, we
detail the corresponding worst-case timing analysis, using the Network Calculus
framework, to infer real-time guarantees. Finally, we conduct the performance
analysis of such a proposal on a realistic AFDX configuration. Results show the
efficiency of the Extended AFDX standard to noticeably enhance the medium
priority level delay bounds, while respecting the higher priority level
constraints, in comparison with the legacy AFDX standard
From Local to Global Stability in Stochastic Processing Networks through Quadratic Lyapunov Functions
We construct a generic, simple, and efficient scheduling policy for
stochastic processing networks, and provide a general framework to establish
its stability. Our policy is randomized and prioritized: with high probability
it prioritizes jobs which have been least routed through the network. We show
that the network is globally stable under this policy if there exists an
appropriate quadratic local Lyapunov function that provides a negative drift
with respect to nominal loads at servers. Applying this generic framework, we
obtain stability results for our policy in many important examples of
stochastic processing networks: open multiclass queueing networks, parallel
server networks, networks of input-queued switches, and a variety of wireless
network models with interference constraints. Our main novelty is the
construction of an appropriate global Lyapunov function from quadratic local
Lyapunov functions, which we believe to be of broader interest.Comment: 39 pages, 4 figure
Smart Jammer and LTE Network Strategies in An Infinite-Horizon Zero-Sum Repeated Game with Asymmetric and Incomplete Information
LTE/LTE-Advanced networks are known to be vulnerable to denial-of-service and
loss-of-service attacks from smart jammers. In this article, the interaction
between a smart jammer and LTE network is modeled as an infinite-horizon,
zero-sum, asymmetric repeated game. The smart jammer and eNode B are modeled as
the informed and the uninformed player, respectively. The main purpose of this
article is to construct efficient suboptimal strategies for both players that
can be used to solve the above-mentioned infinite-horizon repeated game with
asymmetric and incomplete information. It has been shown in game-theoretic
literature that security strategies provide optimal solution in zero-sum games.
It is also shown that both players' security strategies in an infinite-horizon
asymmetric game depend only on the history of the informed player's actions.
However, fixed-sized sufficient statistics are needed for both players to solve
the above-mentioned game efficiently. The smart jammer uses its evolving belief
state as the fixed-sized sufficient statistics for the repeated game. Whereas,
the LTE network (uninformed player) uses worst-case regret of its security
strategy and its anti-discounted update as the fixed-sized sufficient
statistics. Although fixed-sized sufficient statistics are employed by both
players, optimal security strategy computation in {\lambda}-discounted
asymmetric games is still hard to perform because of non-convexity. Hence, the
problem is convexified in this article by devising `approximated' security
strategies for both players that are based on approximated optimal game value.
However, `approximated' strategies require full monitoring. Therefore, a
simplistic yet effective `expected' strategy is also constructed for the LTE
network that does not require full monitoring. The simulation results show that
the smart jammer plays non-revealing and misleading strategies
FATAL+: A Self-Stabilizing Byzantine Fault-tolerant Clocking Scheme for SoCs
We present concept and implementation of a self-stabilizing Byzantine
fault-tolerant distributed clock generation scheme for multi-synchronous GALS
architectures in critical applications. It combines a variant of a recently
introduced self-stabilizing algorithm for generating low-frequency,
low-accuracy synchronized pulses with a simple non-stabilizing high-frequency,
high-accuracy clock synchronization algorithm. We provide thorough correctness
proofs and a performance analysis, which use methods from fault-tolerant
distributed computing research but also addresses hardware-related issues like
metastability. The algorithm, which consists of several concurrent
communicating asynchronous state machines, has been implemented in VHDL using
Petrify in conjunction with some extensions, and synthetisized for an Altera
Cyclone FPGA. An experimental validation of this prototype has been carried out
to confirm the skew and clock frequency bounds predicted by the theoretical
analysis, as well as the very short stabilization times (required for
recovering after excessively many transient failures) achievable in practice.Comment: arXiv admin note: significant text overlap with arXiv:1105.478
Performance Guarantees of Distributed Algorithms for QoS in Wireless Ad Hoc Networks
Consider a wireless network where each communication link has a minimum
bandwidth quality-of-service requirement. Certain pairs of wireless links
interfere with each other due to being in the same vicinity, and this
interference is modeled by a conflict graph. Given the conflict graph and link
bandwidth requirements, the objective is to determine, using only localized
information, whether the demands of all the links can be satisfied. At one
extreme, each node knows the demands of only its neighbors; at the other
extreme, there exists an optimal, centralized scheduler that has global
information. The present work interpolates between these two extremes by
quantifying the tradeoff between the degree of decentralization and the
performance of the distributed algorithm. This open problem is resolved for the
primary interference model, and the following general result is obtained: if
each node knows the demands of all links in a ball of radius centered at
the node, then there is a distributed algorithm whose performance is away from
that of an optimal, centralized algorithm by a factor of at most
. The tradeoff between performance and complexity of the
distributed algorithm is also analyzed. It is shown that for line networks
under the protocol interference model, the row constraints are a factor of at
most away from optimal. Both bounds are best possible
SDN Flow Entry Management Using Reinforcement Learning
Modern information technology services largely depend on cloud
infrastructures to provide their services. These cloud infrastructures are
built on top of datacenter networks (DCNs) constructed with high-speed links,
fast switching gear, and redundancy to offer better flexibility and resiliency.
In this environment, network traffic includes long-lived (elephant) and
short-lived (mice) flows with partitioned and aggregated traffic patterns.
Although SDN-based approaches can efficiently allocate networking resources for
such flows, the overhead due to network reconfiguration can be significant.
With limited capacity of Ternary Content-Addressable Memory (TCAM) deployed in
an OpenFlow enabled switch, it is crucial to determine which forwarding rules
should remain in the flow table, and which rules should be processed by the SDN
controller in case of a table-miss on the SDN switch. This is needed in order
to obtain the flow entries that satisfy the goal of reducing the long-term
control plane overhead introduced between the controller and the switches. To
achieve this goal, we propose a machine learning technique that utilizes two
variations of reinforcement learning (RL) algorithms-the first of which is
traditional reinforcement learning algorithm based while the other is deep
reinforcement learning based. Emulation results using the RL algorithm show
around 60% improvement in reducing the long-term control plane overhead, and
around 14% improvement in the table-hit ratio compared to the Multiple Bloom
Filters (MBF) method given a fixed size flow table of 4KB.Comment: 19 pages, 11 figures, published on ACM Transactions on Autonomous and
Adaptive Systems (TAAS) 201
Information and Memory in Dynamic Resource Allocation
We propose a general framework, dubbed Stochastic Processing under Imperfect
Information (SPII), to study the impact of information constraints and memories
on dynamic resource allocation. The framework involves a Stochastic Processing
Network (SPN) scheduling problem in which the scheduler may access the system
state only through a noisy channel, and resource allocation decisions must be
carried out through the interaction between an encoding policy (who observes
the state) and allocation policy (who chooses the allocation). Applications in
the management of large-scale data centers and human-in-the-loop service
systems are among our chief motivations.
We quantify the degree to which information constraints reduce the size of
the capacity region in general SPNs, and how such reduction depends on the
amount of memories available to the encoding and allocation policies. Using a
novel metric, capacity factor, our main theorem characterizes the reduction in
capacity region (under "optimal" policies) for all non-degenerate channels, and
across almost all combinations of memory sizes. Notably, the theorem
demonstrates, in substantial generality, that (1) the presence of a noisy
channel always reduces capacity, (2) more memory for the allocation policy
always improves capacity, and (3) more memory for the encoding policy has
little to no effect on capacity. Finally, all of our positive (achievability)
results are established through constructive, implementable policies.Comment: 48 pages, 5 figures, 1 tabl
Links as a Service (LaaS): Feeling Alone in the Shared Cloud
The most demanding tenants of shared clouds require complete isolation from
their neighbors, in order to guarantee that their application performance is
not affected by other tenants. Unfortunately, while shared clouds can offer an
option whereby tenants obtain dedicated servers, they do not offer any network
provisioning service, which would shield these tenants from network
interference. In this paper, we introduce Links as a Service, a new abstraction
for cloud service that provides physical isolation of network links. Each
tenant gets an exclusive set of links forming a virtual fat tree, and is
guaranteed to receive the exact same bandwidth and delay as if it were alone in
the shared cloud. Under simple assumptions, we derive theoretical conditions
for enabling LaaS without capacity over-provisioning in fat-trees. New tenants
are only admitted in the network when they can be allocated hosts and links
that maintain these conditions. Using experiments on real clusters as well as
simulations with real-life tenant sizes, we show that LaaS completely avoids
the performance degradation caused by traffic from concurrent tenants on shared
links. Compared to mere host isolation, LaaS can improve the application
performance by up to 200%, at the cost of a 10% reduction in the cloud
utilization.Comment: CCIT Report 888 September 2015, EE Pub No. 1845, Technion, Israe
Communication Complexity of Byzantine Agreement, Revisited
As Byzantine Agreement (BA) protocols find application in large-scale
decentralized cryptocurrencies, an increasingly important problem is to design
BA protocols with improved communication complexity. A few existing works have
shown how to achieve subquadratic BA under an {\it adaptive} adversary.
Intriguingly, they all make a common relaxation about the adaptivity of the
attacker, that is, if an honest node sends a message and then gets corrupted in
some round, the adversary {\it cannot erase the message that was already sent}
--- henceforth we say that such an adversary cannot perform "after-the-fact
removal". By contrast, many (super-)quadratic BA protocols in the literature
can tolerate after-the-fact removal. In this paper, we first prove that
disallowing after-the-fact removal is necessary for achieving
subquadratic-communication BA.
Next, we show new subquadratic binary BA constructions (of course, assuming
no after-the-fact removal) that achieves near-optimal resilience and expected
constant rounds under standard cryptographic assumptions and a public-key
infrastructure (PKI) in both synchronous and partially synchronous settings. In
comparison, all known subquadratic protocols make additional strong assumptions
such as random oracles or the ability of honest nodes to erase secrets from
memory, and even with these strong assumptions, no prior work can achieve the
above properties. Lastly, we show that some setup assumption is necessary for
achieving subquadratic multicast-based BA.Comment: The conference version of this paper appeared in PODC 201
Reliable Broadcast in Practical Networks: Algorithm and Evaluation
Reliable broadcast is an important primitive to ensure that a source node can
reliably disseminate a message to all the non-faulty nodes in an asynchronous
and failure-prone networked system. Byzantine Reliable Broadcast protocols were
first proposed by Bracha in 1987, and have been widely used in fault-tolerant
systems and protocols. Several recent protocols have improved the round and bit
complexity of these algorithms. Motivated by the constraints in practical
networks, we revisit the problem. In particular, we use cryptographic hash
functions and erasure coding to reduce communication and computation complexity
and simplify the protocol design. We also identify the fundamental trade-offs
of Byzantine Reliable Broadcast protocols with respect to resilience (number of
nodes), local computation, round complexity, and bit complexity. Finally, we
also design and implement a general testing framework for similar communication
protocols. We evaluate our protocols using our framework. The results
demonstrate that our protocols have superior performance in practical networks
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