The optimal strategy is defined as one that minimizes the expected cost/throughput ratio, and is allowed to transmit several copies of a packet within a window. We present an algorithm for computing the optimal strategy and study its properties; in particular, we derive bounds on the optimal ...
(of finding the optimal window size) as well, thus establishing an integrated solution algorithm for the strategy optimization problem. Finally, we show that the cost/throughput ratio increases only logarithmically in the time price; this is a signifi- ...
To predict the future’s weather condition, the variation in the conditions in past years must be utilized. The probability that the weather condition of the day in consideration will match the same day in previous year is very less. But the probability
Counting the number of flows present in network traffic is not trivial, given that the naive approach of using a hash table to track the active flows is too slow for the current backbone network speeds. Several algorithms have been proposed in the recent literature that can calculate an approxi...
sahandkhoshdel99/Computer-Networks Star11 Includes Final Project (Python), Wireshark Labs, and Theoretical HWs dnstcpudpchatroomicmparpsmtp-protocolethernetsocket-programmingdistance-vector-routingspanning-tree-protocolsliding-windowleaky-bucket-algorithmtoken-bucket-algorithmdjikstra-algorithmtoken-ringad-hoc-...
Journal 2023, Computer NetworksZijie Zeng, ... Kaimin Wei Mini review A survey on sliding window sketch for network measurement 3.2.1 Sliding Hyperloglog Hyperloglog [84] is an efficient algorithm to estimate the number of distinct elements by using the binary representation of the hashed value of...
A sliding window based algorithm for frequent closed itemset mining over data streams 热度: 1 Position-guidedSliding-windowRouting(PSR)forMobileAd-hocNetworks Konstantinos(Gus)Amouris 1 SymeonPapavassiliou 2∗ ShengXu 2 1 RenaissanceWireless
A relaxation of the sliding window model is the jumping window model [23], where the window does not advance continuously, but discretely in fractions of the measurement window. When operating under this model, we propose the following improvement over the Timestamp Vector algorithm that ...
in order to conduct frequent pattern mining. To address the limitation of fixed sliding windows in adapting to evolving data streams, we propose a variable sliding window frequent pattern mining algorithm, which dynamically adjusts the window size to adapt to new concept drifts and detect them in...
Note that ElephantTrap does not attempt to estimate the size of detected flows, even though it is a light-weight algorithm with random packet sampling. To update the set of sampled packets, we employ a sliding window scheme, where the time window (called sliding window) of a fixed length ...