Lobbying is a legitimate and necessary political instrument in a democratic society. Politics is no longer a process which can be directed (in hierarchical structure only by politicians elected to ...sit in Parliament or in Government. Nowadays, politics has largely become reliant on political counseling and external consultants (lobbyists in different areas of social life (economy, science, etc.. In many developed democracies, lobbying has been institutionalized through the adoption of relevant legislation. In transition countries, in order to lay grounds for the prospective action, it would be necessary (first of all to prepare the society for the process of introducing the concept of lobbying into the legislative framework. In that context, this initial stage may include devising a straightforward and well-prepared public relations strategy which would justify its introduction and most transparently provide for its institutionalization.
Consider a single server queue with i.i.d. arrival and service processes, \{A,\ A_n,n\geq 0\} and \{C,\ C_n,n\geq 0\}, respectively, and a finite buffer B. The queue content process \{Q^B_n,\ n\geq ...0\} is recursively defined as Q^B_{n+1}=\min((Q^B_n+A_{n+1}-C_{n+1})^+,B), q^+=\max(0,q). PUBLICATION ABSTRACT
Consider a finite list of items n = 1, 2,..., N, that are requested according to an i.i.d. process. Each time an item is requested it is moved to the front of the list. The associated search cost ...CNfor accessing an item is equal to its position before being moved. If the request distribution converges to a proper distribution as N → ∞, then the stationary search cost CNconverges in distribution to a limiting search cost C. We show that, when the (limiting) request distribution has a heavy tail (e.g., generalized Zipf's law), P R = n ∼ c/nαas n → ∞, $\alpha >$ 1, then the limiting stationary search cost distribution $\mathbb PC >$ n, or, equivalently, the least-recently used (LRU) caching fault probability, satisfies $\underset{n\rightarrow\infty}{lim}\frac{\mathbb PC > n}{\mathbb PR > n} = (1 - \frac{1}{\alpha})\Gamma(1 - \frac{1}{\alpha})^\alpha \nearrow e^\gamma as\thinspace \alpha \rightarrow \infty,$ where Γ is the Gamma function and γ (=0.5772...) is Euler's constant. When the request distribution has a light tail PR = n ∼ c exp(-λ nβ) as n → ∞ (c, λ, $\beta >$ 0), then $\underset{n\rightarrow\infty}{lim}\frac{\mathbb PC_f > n}{\mathbb PR > n} = e^\gamma,$ independently of c, λ, β, where Cfis a fluid approximation of C. We experimentally demonstrate that the derived asymptotic formulas yield accurate results for lists of finite sizes. This should be contrasted with the exponential computational complexity of Burville and Kingman's exact expression for finite lists. The results also imply that the fault probability of LRU caching is asymptotically at most a factor eγ(≈ 1.78) greater than for the optimal static arrangement.
Space filling and depletion Baryshnikov, Yuliy; Coffman, E. G.; Jelenković, Predrag
Journal of applied probability,
09/2004, Volume:
41, Issue:
3
Journal Article
Peer reviewed
For a given k ≥ 1, subintervals of a given interval 0, X arrive at random and are accepted (allocated) so long as they overlap fewer than k subintervals already accepted. Subintervals not accepted ...are cleared, while accepted subintervals remain allocated for random retention times before they are released and made available to subsequent arrivals. Thus, the system operates as a generalized many-server queue under a loss protocol. We study a discretized version of this model that appears in reference theories for a number of applications, including communication networks, surface adsorption-desorption processes, and reservation systems. Our primary interest is in steady-state estimates of the vacant space, i.e. the total length of available subintervals kX - ∑ℓ
i
, where the ℓ
i
are the lengths of the subintervals currently allocated. We obtain explicit results for k = 1 and for general k with all subinterval lengths equal to 2, the classical dimer case of chemical applications. Our focus is on the asymptotic regime of large retention times.
Hidden Markov processes such as the Gilbert-Elliott (1960) channel have an infinite dependency structure. Therefore, entropy and channel capacity calculations require knowledge of the infinite past. ...In practice, such calculations are often approximated with a finite past. It is commonly assumed that the approximations require an unbounded amount of the past as the memory in the underlying Markov chain increases. We show that this is not necessarily true. We derive an exponentially decreasing upper bound on the accuracy of the finite-past approximation that is much tighter than existing upper hounds when the Markov chain mixes well. We also derive an exponentially decreasing upper bound that applies when the Markov chain does not mix at all. Our methods are demonstrated on the Gilbert-Elliott channel, where we prove that a prescribed finite-past accuracy is quickly reached, independently of the Markovian memory. We conclude that the past can be used either to learn the channel state when the memory is high, or wait until the states mix when the memory is low. Implications fur computing and achieving capacity on the Gilbert-Elliott channel are discussed.
In this paper we deal with the role and importance of communication in increasing the efficiency of the Republic Agency for the Peaceful Settlement of Labor Disputes. Although communication is ...ubiquitous, it is often not accessed systematically and its role and place in the functioning of the organization is ignored. Based on the analysis and research in the paper, it is shown that through a systemic approach to communication in the work of one state body, there has been greater efficiency. Communication is analyzed in procedures and methods of peaceful settlement of labor disputes, arbitration and mediation, as well as with users of services of Agency, primarily the civil society. It also points to the basic indicators of the contribution of the improved communicator to the number of procedures and statistical parameters.
Consider a generic data unit of random size L that needs to be transmitted over a channel of unit capacity. The channel dynamics is modeled as an on-off process {(Ai, E/j)}iles1 with alternating ...independent periods when channel is available A i and unavailable U i , respectively. During each period of time that the channel becomes available, say A i , we attempt to transmit the data unit. If L les A i , the transmission was considered successful; otherwise, we wait for the next period A i+i when the channel is available and attempt to retransmit the data from the beginning. We study the asymptotic properties of the total transmission time T and number of retransmissions N until the data is successfully transmitted. In recent studies it was proved that the waiting time T follows a power law when the distributions of L and A 1 are of an exponential type, e.g., Gamma distribution. In this paper, we show that the distributions of N and T follow power laws with exponent alpha as long as logPL > x apalphalogPA 1 > x for large x. Hence, it may appear surprising that we obtain power law distributions irrespective of how heavy or light the distributions of L and A 1 may be. In particular, both L and A 1 can decay faster than any exponential, which we term superexponential. For example, if L and A 1 are Gaussian with variances sigma 2 L and sigma 2 A , respectively, then N and T have power law distributions with exponent alpha = sigma 2 A /sigma 2 L ; note that, if sigma 2 A <sigma 2 L , the transmission time has an infinite mean and, thus, the system is unstable. The preceding model, as recognized in (Fiorini et al., 2005), describes a variety of situations where failures require jobs to restart from the beginning. Here, we identify that this model also provides a new mechanism for explaining the frequently observed power law phenomenon in data networks. Specifically, we argue that it may imply the power laws on both the application as well as the data link layer, where variable-sized documents and (IP) packets are transmitted, respectively. We discuss the engineering ramifications of our observations, especially in the context of wireless ad hoc and sensor networks where channel failures are frequent. Furthermore, our results provide an easily computable benchmark for measuring the matching between the data and channel characteristics that permits/prevents satisfactory transmission.
A precise asymptotic relation between the Palm queue distribution and the time average queue distribution is established for a simple subexponential on-off fluid flow queue. A queueing system in ...which one on-off source, whose on period belongs to a subclass of subexponential distributions, is multiplexed with independent exponential sources with an aggregate expected rate Ee sub(t) asymptotically equivalent to the same queueing system with the exponential arrival process being replaced by the total mean value Ee sub(t). For fluid queue with the limiting M/G/ infinity arrivals, a tight asymptotic lower bound for large buffer probabilities is obtained.
Adaptive and scalable comparison scheduling Jelenkovic, Predrag R.; Kang, Xiaozhu; Tan, Jian
ACM SIGMETRICS 2007: the International Conference on Measurement and Modeling of Computer Systems; San Diego, CA; USA; 12-16 June 2007,
06/2007, Volume:
35, Issue:
1
Journal Article, Conference Proceeding
The Shortest Remaining Processing Time (SRPT) scheduling disciplineis optimal and its superior performance, compared with the policies that do not use the knowledge of job sizes, can be quantified ...using mean-value analysis as well as our new a symptotic distribution allimits for the relatively smaller heavy-tailed jobs. However, the main difficulty in implementing SRPT in large practical systems, e.g., Web servers, is that its complexity grows with the number of jobs in the queue. Hence, in order to lower the complexity, it is natural to approximate SRPT by grouping the arrivals into a fixed (small) number of classes containing jobs of approximately equal size and then serve the classes of smaller jobs with higher priorities.
In this paper, we design a novel adaptive grouping mechanism based on relative size comparison of a newly arriving job to the preceding
m
arrivals. Specifically, if the newly arriving job is smallerthan
k
and larger than
m-k
of the previous
m
jobs, it isrouted into class
k
. The excellent performance of this mechanism,even for a small number of classes
m
+1, is demonstrated using both the asymptotic queueing analysis under heavy tails and extensive simulations. We also discuss refinements of the comparison grouping mechanism that improve the accuracy of job classification at the expense of a small additional complexity.
PDF
