Note that in the above equations, the $R_{sp}(b_j)$, $\forall b_j \in B$, $RB^M(u_i)$, $\forall u_i \in U$, and $RB^S(u_i)$, $\forall u_i \in U$, are unknown variables. The objective function of the above formulation is to maximize the estimated total amount of data, i.e., to maximize the network throughput. The constraint C1 restricts the split data rate $R_{sp}(b_j)$, $\forall b_j \in B^C$, should be less than $b_j$'s input data rate $R_{in}(b_j)$. The C2 demands that the $D^M_p(u_i)$ cannot be larger than the summation of (i) UE $u_i$'s input data volume at MeNB in the upcoming $I_t$, i.e., $R_{agg}^M(u_i) \times I_t$ and (ii) the remaining data located at MeNB $D_r^M(u_i)$. The C3 restricts the $D^S_p(u_i)$ on SeNBs, and the idea is similar …show more content…
In our simulations, there are one MeNB and one SeNB, and the distance between MeNB and SeNB is 1 km. All UEs are assumed to have dual connectivity capability, and their initial locations are randomly assigned. A UE can connect to the SeNB if the detected signal strength on that SeNB is larger than $-75$ dBm. Each UE is configured to have one bearer, and the traffic type of the bearer is constant bit rate (CBR). For a UE, it may receive data from MeNB, SeNB or both of MeNB and SeNB depending on its location or the decisions of our traffic scheduler. We observe the network throughput (in Mbps) by varing the following four parameters: (i) The numer of UE, say $N_{ue}$. (ii) Per UE's CBR traffic data rate, say $R_{cbr}$, in unit of kbps. (iii) Per UE's random walk speed, say $V_{walk}$, in unit of km/hr. (iv) The transmission power of the SeNB, say $P_{senb}$, in unit of dBm. The proposed traffic scheduler works every 100 TTIs, i.e., we set $I_t=100$ ms. Other system parameters are listed in \Tab{tab:dis_para}. Furthermore, we compare the proposed scheme with the fix traffic scheduling in \cite{132859}. Recall that in \cite{132859}, $x\%$ (resp., $(1-x)\%$) of per UE's traffics will be handled by the MeNB (resp., SeNB). In our simulations, we set $x$ to be 100, 70, 50, 30, and 0 (denoted by F(100), F(70), …show more content…
We can see that the proposed scheduling scheme (denoted by OUR) can perform the best in all cases. In this simulation, when a UE is located near the boundary of the SeNB, the reported CQI values of the UE will be small. But, when using fixed traffic scheduling, the MeNB still asks the SeNB to relay $1-x\%$ of parckets to that UE, and thus degrades the network throughput. We can see that when $R_{cbr}$ values are lower, the network throughput of F(100) can be better than that of F($x$), where $x=70, 50, 30, 0$. This is because that the MeNB has a larger coverage range, if the MeNB handles most traffics, the network throughput will likely to be better. But, when $R_{cbr}$ becomes larger, F(70) can perform better because that the MeNB is overloaded, and the SeNB can help to increase some extra throughput. Moreover, \Fig{fig:dis_sim_var}(b) shows the result that we vary $P_{senb}$ from 18 to 28 dBm, and fix $N_{ue}=50$, $R_{cbr}=400$, and $V_{walk}=6$. We can see that when $P_{senb}$ becomes larger, the performance gaps between OUR and the fixed scheduling will be smaller. This is because that when using a larger $P_{senb}$, the SeNB has more chances to serve UEs, and thus the network throughput can be improved. Furthermore, we also observe the network throughput by varying $N_{ue}$ and $V_{walk}$. (The results are not shown because of lacking spaces.) The
• A cluster head is chosen when the network is first activated. • As a node drains its battery power totally, it becomes dead and is eliminated from the network. Calculating Node Weight: Distance traveled by a node Dv = sum [DISTv] In ‘n’ time units from i= t-n to i= t where t is the current time.
BU275 Assignment 2 Equations Question 1 A Station 1: Prep Inter-arrival time is the time between consecutive arrivals of the customers. Because the inter-arrival times are exponentially distributed, customers arrive at random times. The mean is 100 customers/ hours. This indicates that a customer arrives every 0.6 minutes.
As IGRP, “uses bandwidth to determine how to load balance.” Based on this theory IGRP can distribute packets across and prioritise when there is a faster available or a more suitable path should a link delay or fail due to the heavy amount of traffic which may be passing through the router. Link State 1. In link-state routing, routers do maintain a map of the network.
However, significant overheads in terms of communication and storage are incurred due to the flooding or multi-hop forwarding [10, 11]. 3) Without the network infrastructure, steady connection between nodes is difficult to be guaranteed, especially in large scale VANETs. In other words, the scalability is difficult
A sensor node must route traffic according to QoS requirements as stated below: 1) Priority level based route traffic. 2) Reduce delay to relay event-based packets. 3) Ensure event alerts delivery.
a). Based on the observation, we assume that the distance between two stations is 0.375 KM Mean time to send = propogation time + transmission time = 375m. + 1000bits 200 x 106 m/sec. 10 000 000 bps. = 102 μsec. b).
Task 1 1.1) Design a networked system to meet the given specification. Your design must satisfy the user requirements and be scalable. [3.1] The design of the network system should include: cost, Bandwidth, system growth, applications, communications, and scalability of the system and selection of components. Introduction - Designing the Network In this design I will be listing and discussing, through the different and necessary designing stages, the various elements involved in designing a network that meets the system requirements given by the client.
Parrish, We have a green light. One additional requirement, is that risk assessment team works with MAT to complete the following: 1) Work in tandem with Fred to "develop a criteria / written documentation to assess Wi-Fi access points (WAP) devices so when the risk assessors go out to perform their assessments that validation understands what to ask for and how to validate these devices for CS security to include "best practice" mitigation hardening for these devices. 2) Find out where all these Wi-Fi WAPs are included in the packages. Our database could be of use to them. (E.g. FARs comes to my mind as I know they use WAP) In additional, have them find out who else uses WAPs?
In semi-structured P2P network, the super-peers manage and organise the reputation values of their peers for resource selection and enhancing the result merging results. The reputation values of peers, however, are calculated by aggregating its documents ' reputation values. Technically, the super-peers build a 2-tuple of peer and documents reputation vector as esizebox{0.27 extwidth}{!}{$(P_{i}, (Rep(d_{1}), Rep(d_{2}), ..., Rep(d_{n})))$} where $P_{i}$ is peer $i$ belong to super-peer $S_{j}$ and $Rep(d_{k})$ refers to the document reputation value as calculated in Equation ef{Reputation_documents}. The peer 's reputation value is aggregated from other users ' feedbacks on its documents as in Equation ef{RepPeer}. egin{equation} Rep(P_{j})
First of all, I read the reading topics assigned in the "Learning Guide Unit 1" particularly the Boolean functions, Boolean algebra, different types of logic gates and its composition, truth table, etc. However, I followed all of the reading topics assigned. Apart from the reading topics, I also go through the video lectures. Then after, I attempted "Self-Quiz Unit 1", completed "Unit 1 Assignment" related to creating different types of Logic gates. Finally, took part on the "Discussion Forum Unit 1", commented on three colleagues' post, and graded them.
Before discussing to the simulation results, we would like to have a glimpse of the assumptions and major parameters: 1) OPNET simulator[31] is used to generate 100 sensor nodes for a CR-WMSNs. Initially, the connectivity of the CR-WMSNs is kept as 0.7. The capacity of the network links is assumed to be Poisson distribution with mean 100 kbps. Every sensor is assumed to
Annotated Bibliography Kim, C., Caesar, M., & Rexford, J. (2011). Seattle: A scalable Ethernet architecture for large enterprises. ACM Transactions on Computer Systems, 29(1), [1]. Doi: 10.1145/1925109.1925110 The purpose of this white paper is to present a comprehensive solution to a critical flaw in the way Internet Protocol (IP) based networks are designed with the current practices already well vetted.
Each vehicle must proceed from the garage to service the tasks and finally back to the garage; 2). Each task can only be serviced by one vehicle and only be serviced once; 3). The total demand of the tasks which is serviced by each vehicle does not exceed its capacity Q. In the above three constraints, constraints 1), and 2) are the fundamental constraints that exists in all arc routing problem. However, constraint 3) is
A node is selected as a cluster head if its weight is higher than any of its neighbor’s weight; otherwise, it joins a neighboring cluster-head. The smaller weighted node ID is chosen in case of an equality. The DCA makes an assumption that the network topology does not change during the execution of the algorithm. Since node weights were different in each simulation cycle, identifying the cluster-heads becomes very expensive and there are no optimizations on the system parameters such as throughput and power control.
Thus, atleast 2N-2 wavelengths are required for the above connections. At this point, when a new connection of the form arrives, it needs another new wavelength. Thus, atleast wavelengths are required for this worst case multicast assignment. Therefore, 2N-1 wavelengths are sufficient and necessary for a WRMD WDM unidirectional ring with N node to be wide-sense nonblocking for any multicast assignment.