20 research outputs found
Analysis of Slotted ALOHA with Multipacket Messages in Clustered Surveillance Networks
This work presents an analysis of a cluster of finite population of low cost sensor nodes operating in a p-persistent S-Aloha framework with multipacket messages. Using this analytical framework, we consider the issue of partitioning the nodes and available frequencies into groups so as to maximize the system throughput. Assigning the nodes and frequencies into âgroupsâ is important because the size of the group impacts the tradeoff between the benefits of frequency diversity and the cost of collision on the shared medium imposed by the nodes in a group. We study this tradeoff through analytical and numerical results and show how the correct choice of group sizes can vary depending on various factors like the ratio of nodes to frequencies and the overall system load
Strategic Contention Resolution in Multiple Channels
We consider the problem of resolving contention in communication networks
with selfish users. In a \textit{contention game} each of identical
players has a single information packet that she wants to transmit using one of
multiple-access channels. To do that, a player chooses a
slotted-time protocol that prescribes the probabilities with which at a given
time-step she will attempt transmission at each channel. If more than one
players try to transmit over the same channel (collision) then no transmission
happens on that channel. Each player tries to minimize her own expected
\textit{latency}, i.e. her expected time until successful transmission, by
choosing her protocol. The natural problem that arises in such a setting is,
given and , to provide the players with a common, anonymous protocol (if
it exists) such that no one would unilaterally deviate from it (equilibrium
protocol).
All previous theoretical results on strategic contention resolution examine
only the case of a single channel and show that the equilibrium protocols
depend on the feedback that the communication system gives to the players. Here
we present multi-channel equilibrium protocols in two main feedback classes,
namely \textit{acknowledgement-based} and \textit{ternary}. In particular, we
provide equilibrium characterizations for more than one channels, and give
specific anonymous, equilibrium protocols with finite and infinite expected
latency. In the equilibrium protocols with infinite expected latency, all
players transmit successfully in optimal time, i.e. , with
probability tending to 1 as .Comment: The results of this work are included in the 11th International
Symposium on Algorithmic Game Theory (SAGT 2018) and the 16th Workshop on
Approximation and Online Algorithms (WAOA 2018
Modeling Slotted Aloha as a Stochastic Game with Random Discrete Power Selection Algorithms
We consider the uplink case of a cellular system where bufferless mobiles transmit over a common channel to a base station, using the slotted aloha medium access protocol. We study the performance of this system under several power differentiation schemes. Indeed, we consider a random set of selectable transmission powers and further study the impact of priorities given either to new arrival packets or to the backlogged ones. Later, we address a general capture model where a mobile transmits successfully a packet if its instantaneous SINR (signal to interferences plus noise ratio) is lager than some fixed threshold. Under this capture model, we analyze both the cooperative team in which a common goal is jointly optimized as well as the noncooperative game problem where mobiles reach to optimize their own objectives. Furthermore, we derive the throughput and the expected delay and use them as the objectives to optimize and provide a stability analysis as alternative study. Exhaustive performance evaluations were carried out, we show that schemes with power differentiation improve significantly the individual as well as global performances, and could eliminate in some cases the bi-stable nature of slotted aloha
Markov Decision Processes with Applications in Wireless Sensor Networks: A Survey
Wireless sensor networks (WSNs) consist of autonomous and resource-limited
devices. The devices cooperate to monitor one or more physical phenomena within
an area of interest. WSNs operate as stochastic systems because of randomness
in the monitored environments. For long service time and low maintenance cost,
WSNs require adaptive and robust methods to address data exchange, topology
formulation, resource and power optimization, sensing coverage and object
detection, and security challenges. In these problems, sensor nodes are to make
optimized decisions from a set of accessible strategies to achieve design
goals. This survey reviews numerous applications of the Markov decision process
(MDP) framework, a powerful decision-making tool to develop adaptive algorithms
and protocols for WSNs. Furthermore, various solution methods are discussed and
compared to serve as a guide for using MDPs in WSNs
Emerging Communications for Wireless Sensor Networks
Wireless sensor networks are deployed in a rapidly increasing number of arenas, with uses ranging from healthcare monitoring to industrial and environmental safety, as well as new ubiquitous computing devices that are becoming ever more pervasive in our interconnected society. This book presents a range of exciting developments in software communication technologies including some novel applications, such as in high altitude systems, ground heat exchangers and body sensor networks. Authors from leading institutions on four continents present their latest findings in the spirit of exchanging information and stimulating discussion in the WSN community worldwide
Multi-attribute demand characterization and layered service pricing
As cloud computing gains popularity, understanding the pattern and structure of its workload is increasingly important in order to drive effective resource allocation and pricing decisions. In the cloud model, virtual machines (VMs), each consisting of a bundle of computing resources, are presented to users for purchase. Thus, the cloud context requires multi-attribute models of demand. While most of the available studies have focused on one specific attribute of a virtual request such as CPU or memory, to the best of our knowledge there is no work on the joint distribution of resource usage. In the first part of this dissertation, we develop a joint distribution model that captures the relationship among multiple resources by fitting the marginal distribution of each resource type as well as the non-linear structure of their correlation via a copula distribution. We validate our models using a public data set of Google data center usage.
Constructing the demand model is essential for provisioning revenue-optimal configuration for VMs or quality of service (QoS) offered by a provider. In the second part of the dissertation, we turn to the service pricing problem in a multi-provider setting: given service configurations (qualities) offered by different providers, choose a proper price for each offered service to undercut competitors and attract customers. With the rise of layered service-oriented architectures there is a need for more advanced solutions that manage the interactions among service providers at multiple levels. Brokers, as the intermediaries between customers and lower-level providers, play a key role in improving the efficiency of service-oriented structures by matching the demands of customers to the services of providers. We analyze a layered market in which service brokers and service providers compete in a Bertrand game at different levels in an oligopoly market while they offer different QoS. We examine the interaction among players and the effect of price competition on their market shares. We also study the market with partial cooperation, where a subset of players optimizes their total revenue instead of maximizing their own profit independently. We analyze the impact of this cooperation on the market and customers' social welfare
Markov decision processes with applications in wireless sensor networks: A survey
Ministry of Education, Singapore under its Academic Research Funding Tier