1,536 research outputs found
Active Queue Management for Fair Resource Allocation in Wireless Networks
This paper investigates the interaction between end-to-end flow control and MAC-layer scheduling on wireless links. We consider a wireless network with multiple users receiving information from a common access point; each user suffers fading, and a scheduler allocates the channel based on channel quality,but subject to fairness and latency considerations. We show that the fairness property of the scheduler is compromised by the transport layer flow control of TCP New Reno. We provide a receiver-side control algorithm, CLAMP, that remedies this situation. CLAMP works at a receiver to control a TCP sender by setting the TCP receiver's advertised window limit, and this allows the scheduler to allocate bandwidth fairly between the users
Live Prefetching for Mobile Computation Offloading
The conventional designs of mobile computation offloading fetch user-specific
data to the cloud prior to computing, called offline prefetching. However, this
approach can potentially result in excessive fetching of large volumes of data
and cause heavy loads on radio-access networks. To solve this problem, the
novel technique of live prefetching is proposed in this paper that seamlessly
integrates the task-level computation prediction and prefetching within the
cloud-computing process of a large program with numerous tasks. The technique
avoids excessive fetching but retains the feature of leveraging prediction to
reduce the program runtime and mobile transmission energy. By modeling the
tasks in an offloaded program as a stochastic sequence, stochastic optimization
is applied to design fetching policies to minimize mobile energy consumption
under a deadline constraint. The policies enable real-time control of the
prefetched-data sizes of candidates for future tasks. For slow fading, the
optimal policy is derived and shown to have a threshold-based structure,
selecting candidate tasks for prefetching and controlling their prefetched data
based on their likelihoods. The result is extended to design close-to-optimal
prefetching policies to fast fading channels. Compared with fetching without
prediction, live prefetching is shown theoretically to always achieve reduction
on mobile energy consumption.Comment: To appear in IEEE Trans. on Wireless Communicatio
Principles of Physical Layer Security in Multiuser Wireless Networks: A Survey
This paper provides a comprehensive review of the domain of physical layer
security in multiuser wireless networks. The essential premise of
physical-layer security is to enable the exchange of confidential messages over
a wireless medium in the presence of unauthorized eavesdroppers without relying
on higher-layer encryption. This can be achieved primarily in two ways: without
the need for a secret key by intelligently designing transmit coding
strategies, or by exploiting the wireless communication medium to develop
secret keys over public channels. The survey begins with an overview of the
foundations dating back to the pioneering work of Shannon and Wyner on
information-theoretic security. We then describe the evolution of secure
transmission strategies from point-to-point channels to multiple-antenna
systems, followed by generalizations to multiuser broadcast, multiple-access,
interference, and relay networks. Secret-key generation and establishment
protocols based on physical layer mechanisms are subsequently covered.
Approaches for secrecy based on channel coding design are then examined, along
with a description of inter-disciplinary approaches based on game theory and
stochastic geometry. The associated problem of physical-layer message
authentication is also introduced briefly. The survey concludes with
observations on potential research directions in this area.Comment: 23 pages, 10 figures, 303 refs. arXiv admin note: text overlap with
arXiv:1303.1609 by other authors. IEEE Communications Surveys and Tutorials,
201
Multiuser Scheduling in a Markov-modeled Downlink using Randomly Delayed ARQ Feedback
We focus on the downlink of a cellular system, which corresponds to the bulk
of the data transfer in such wireless systems. We address the problem of
opportunistic multiuser scheduling under imperfect channel state information,
by exploiting the memory inherent in the channel. In our setting, the channel
between the base station and each user is modeled by a two-state Markov chain
and the scheduled user sends back an ARQ feedback signal that arrives at the
scheduler with a random delay that is i.i.d across users and time. The
scheduler indirectly estimates the channel via accumulated delayed-ARQ feedback
and uses this information to make scheduling decisions. We formulate a
throughput maximization problem as a partially observable Markov decision
process (POMDP). For the case of two users in the system, we show that a greedy
policy is sum throughput optimal for any distribution on the ARQ feedback
delay. For the case of more than two users, we prove that the greedy policy is
suboptimal and demonstrate, via numerical studies, that it has near optimal
performance. We show that the greedy policy can be implemented by a simple
algorithm that does not require the statistics of the underlying Markov channel
or the ARQ feedback delay, thus making it robust against errors in system
parameter estimation. Establishing an equivalence between the two-user system
and a genie-aided system, we obtain a simple closed form expression for the sum
capacity of the Markov-modeled downlink. We further derive inner and outer
bounds on the capacity region of the Markov-modeled downlink and tighten these
bounds for special cases of the system parameters.Comment: Contains 22 pages, 6 figures and 8 tables; revised version including
additional analytical and numerical results; work submitted, Feb 2010, to
IEEE Transactions on Information Theory, revised April 2011; authors can be
reached at [email protected]/[email protected]/[email protected]
Energy Optimal Transmission Scheduling in Wireless Sensor Networks
One of the main issues in the design of sensor networks is energy efficient
communication of time-critical data. Energy wastage can be caused by failed
packet transmission attempts at each node due to channel dynamics and
interference. Therefore transmission control techniques that are unaware of the
channel dynamics can lead to suboptimal channel use patterns. In this paper we
propose a transmission controller that utilizes different "grades" of channel
side information to schedule packet transmissions in an optimal way, while
meeting a deadline constraint for all packets waiting in the transmission
queue. The wireless channel is modeled as a finite-state Markov channel. We are
specifically interested in the case where the transmitter has low-grade channel
side information that can be obtained based solely on the ACK/NAK sequence for
the previous transmissions. Our scheduler is readily implementable and it is
based on the dynamic programming solution to the finite-horizon transmission
control problem. We also calculate the information theoretic capacity of the
finite state Markov channel with feedback containing different grades of
channel side information including that, obtained through the ACK/NAK sequence.
We illustrate that our scheduler achieves a given throughput at a power level
that is fairly close to the fundamental limit achievable over the channel.Comment: Accepted for publication in the IEEE Transactions on Wireless
Communication
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