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HARVEY: So you were willing to bid your entire trading account for the chance to win an indefinite amount ME: That sounds horrible HARVEY: And it sounds like the truth ME: I remember what you said about George Sisler and his first experience managing money I don t want to compare myself to a successful trader like George, but this does sound familiar At a point, he stopped knowing what he was in the trade for and he kept the trade open just to not lose He was, for a while, willing to lose an infinite sum of money in order to win an indefinite profit HARVEY: You remember George now! But you did not remember him this morning ME: I did forget George completely HARVEY: That s because it happened to George! Now we re getting someplace.

(7.5)

Information Source Source bitstream Burstiness Isochronism Burst parameters Tolerance Service quality Bit error-related Delay-related Buffer-related Availability Quantity Timeliness Assuredness Cost

(7.6)

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across discontinuities of physical access create a perception of seamlessness. Seamlessness may also require ef ciency, balancing battery power, RF spectrum, data rate, and radiated power to the degree necessary for QoI. Using That Knowledge: The MBMMR-expert AACR reasons about the differences among physical access, propagation path impairments, spectrum allocations, air interfaces, and information services from HF through EHF including SATCOM. It employs this knowledge to proactively enhance QoI via the appropriate band and mode, reacting appropriately to changes in the user s behavior. It should be able to differentiate exceptions such as working into lunch from the norm of entertainment during lunch. Cultural stereotypes re ect the prototypical behavior of many of the people some of the time, but rarely will cultural stereotypes be satisfactory to any given user. The iCM therefore learns user preferences in the timing and use of the bands and modes, removing from the user the burden of learning the radio nuances.

Since a single route per connection is the desirable in the majority of the networks, the authors add integer ow constraints to facilitate such a routing con guration. Model Components. In contrast to the con ict graph models used in Jain et al. [49] and the edge-based approach in Kodialam and Nandagopal [51] the formulation in Kolar and Abu-Ghazaleh [52] adopts node-based interference model where interference at a given node, rather than at a link, is calculated. Such a formulation aids in approximation of the distributed protocol rules based on the observed behavior at the nodes. The busy time of each node i is calculated accounting for all the traf c on the interfering links which is denoted by Ii . Since interference at edges that are not active is immaterial, the notion of normalized interference (denoted by Ii ) is introduced. Normalized interference (Ii ) at a node i is set to the interference observed at the node (Ii ) if the node is active, otherwise, it is set to zero. The total amount of time to accommodate the local traf c carried by the node (Si ) in addition to normalized interference observed is termed the commitment period of the node and is represented by Ai . Commitment period represents the amount of time the node is busy to accommodate local traf c or interfering traf c. Optimality Formulation. Kolar and Abu-Ghazaleh [52] also explore objective function issues in their formulation. For an interference aware routing formulation, reasonable objectives include: (1) minimizing the interference experienced by each route and (2) reducing the interference interactions among different routes. The interference across each individual ow has to be minimized, thus resulting in an objective

When you become a great trader, these lessons will not be far off in your mind You ll remember what you did this morning much more clearly than what happened to George..

function for each ow. However, solving linear programming formulations against multiple objectives is known to be computationally dif cult. Thus, there is a need for a single objective function that captures the overall network performance without sacri cing individual connection performance. Equation (7.7) states a simple objective function to minimize the commitment period of all the nodes, and Eq. (7.8) is an objective function to minimize the hot-spot node that has the highest commitment period. Minimize Minimize

Network Knowledge Network ALE CB, Ham Air traf c control Cellular bands PSTN core Cellular backhaul DVB, DAB Typical and Unique Knowledge Set up, tear down, TCP/IP interoperability Voice interoperability User credentials, verbal protocol Legacy 1 G, 2 G, 3 G services, licensing, tariffs Link protocols, SS7, IP (MPLS) Ad hoc interoperability for humanitarian relief Channels, licensing, security waveforms

(7.7) (7.8)

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