Resource Management in Satellite Networks part 24 doc

Figure 7.4 [20] represents call blocking, call dropping due to a temporary lack of bandwidth and cell loss probabilities for three different allocation strategies: i cross-layer Optimize

when they are applied In particular:

• “Greedy” traffic flows can compromise the whole satellite system’s QoS.

• Compatibility between different control techniques and bandwidth request

methods should be validated

• Security issues on the signaling channel should be analyzed in order to

prevent denial of service attacks based on fake bandwidth reservations Those issues should be investigated and carefully addressed before using DBA techniques in any actual system

7.3.2 Dynamic bandwidth de-allocation

Several approaches for bandwidth and handover management have been studied in the recent literature in the case of mobile satellite systems Publications in this area investigate only bandwidth allocation and the intra-satellite handover management In reference [18], an advanced bandwidth management strategy is proposed and evaluated, allowing for bandwidth allo-cation/deallocation and a novel inter-satellite handover management scheme, tailored for multimedia LEO satellite networks with satellite diversity The main mechanism is based on bandwidth de-allocation According to the proposed scheme, capacity reservation requests for handover calls are removed from the queues when the capacity that they strive to reserve is unlikely

to be used Simulations confirmed the usefulness of bandwidth de-allocation mechanism Other details of this scheme have been already discussed in sub-Section 6.4

7.3.3 Dynamic bandwidth allocation with cross-layer issues

Some examples of cross-layer DBA schemes are here briefly discussed, limiting the description to recent works [19]-[25] An overview of cross-layer approaches

Fig 7.3: DBA in GEO satellite systems.

coefficients” [representing the inverse of the ratios of the Information Bit Rate (IBR) in the specific channel condition to the one in clear sky] Various

methods have been considered for bandwidth allocation, and the overall structure has been evaluated in the presence of real fading traces [19],[20] Figure 7.4 [20] represents call blocking, call dropping (due to a temporary lack of bandwidth) and cell loss probabilities for three different allocation

strategies: (i ) cross-layer Optimized Centralized (OC, where the bandwidth

is allocated on demand by the master station, which solves a centralized

optimization problem); (ii ) cross-layer Optimized Proportional (OP, where

optimal allocation requests are computed locally by the Earth stations and then passed to the master, which re-scales them and distributes the bandwidth

proportionally); (iii ) Simple Proportional (SP, based on offered load, with

no cross-layer dynamic allocation) The reported results refer to a 10,000 s simulation, with 10 Earth stations, 5 of which experience different fading conditions, whereas 5 operate in clear sky In these graphs, the probabilities for each point in time are computed by averaging over all stations in the system, and over a time window of 1,000 s The fading is dynamically variable, according to real traces

The advantage of the cross-layer allocations lies in maintaining blocking probability values below a given threshold (5% in the specific case), while minimizing the call dropping and the BE traffic cell loss probabilities in the stations’ buffers

The second example deals with DBA in the presence of only inelastic packet traffic with two stations, whose traffic loads periodically alternate between a lower and a higher value Figure 7.5 [22] illustrates the convergence

properties of a gradient descent technique, based on Infinitesimal Perturbation Analysis (IPA) [21]-[23] Station 2 is in clear sky, whereas station 1 also

experiences fading variations, besides those in traffic load The bandwidth allocation provided by the IPA gradient estimation, based only on on-line measurements, is capable to face both dynamic effects in order to minimize

Fig 7.4: Call blocking and dropping (left) and cell loss (right) probabilities.

These graphs are reproduced from “Adaptive Cross-layer Bandwidth Allocation in a Rain-faded

Satellite Environment”, N Celandroni, F Davoli, E Ferro, A Gotta, International Journal of Communication Systems, Vol 19 No 5, pp 509–530, June 2006 c 2006 Copyright John Wiley

& Sons Limited Reproduced with permission.

Fig 7.5: IPA gradient descent allocation, under traffic load and fade changes See

reference [22] Copyright c2006 IEEE.

the overall loss volume

The problem considered in [21],[22] is a pure parametric optimization In order to avoid transient periods in the convergence of the on-line gradient

descent technique, a different point of view can be adopted [23] where open-loop feedback control strategies (i.e., stemming from a functional optimization

approach) are approximated by means of neural networks

Finally, a DBA cross-layer optimization, aiming at achieving the “best” compromise between the TCP goodput maximization and fairness, has been treated in [24],[25], in a GEO bent-pipe satellite scenario The numerical details of the example shown here are the same as in [25], with a combination

• The “merge” strategy is the best choice between two alternative methods

(“tradeoff” and “range”, respectively) that establish a balance between goodput and fairness;

• The “proportionally fair” technique maximizes the sum of the logarithms

of the individual goodputs, so as to attain a Nash Bargaining Solution

(NBS);

• The “BER threshold” strategy simply adjusts the redundancy to keep

always BER below a given limit, and assigns the bandwidths proportion-ally to the redundancy and the number of connections of each class (no cross-layer action)

The advantages of the cross-layer strategies, shown in detail in [25], are not only in terms of goodput, but also in terms of fairness

7.3.4 Joint timeslot optimization and fair dynamic bandwidth allocation in a system employing adaptive coding

In [29], an enhanced and multi-beam DVB-RCS system is addressed,

consid-ering both Adaptive Coding (AC) and dynamic framing AC arises when the

transmission is severely affected by channel conditions (as in the Ka band)

In order to keep the link active, framing design must be flexible enough

to adapt in time and frequency, to allow for the use of different carriers

(this technique is also known as Dynamic Resource Allocation, DRA) and/or

different protection-levels of channel coding (AC)

The problem of optimal framing has been already addressed in the literature For example, in [30] a method is presented for optimal super-frame pattern design for the DVB-RCS MF-TDMA return link, so that the system data throughput is maximized The authors formulate the design problem

as a non-linear combinatorial optimization problem However, the developed

method considers static framing and, therefore, it is not extensible to Ka band

Fig 7.6: Merge, Proportionally Fair and BER Threshold (thr = 10−6) strategies.

A class in fading (a); a class in clear sky (b) See reference [25] Copyright c 2006

IEEE

in the frames can be of various durations, according to the chosen coding rate; users can be granted slots of different durations on different carriers (sequentially) Differently from other studies, bandwidth is segmented not only in the presence of different traffic types, but also assuming realistic dynamic weather conditions, to which coding rate is adapted

Capacity is allocated giving priority to heavy rain-affected users, then considering less affected ones, and ending with clear sky users, while there is still bandwidth available The major issue to keep into account concerns the limits of capacity that can be allocated, due to adaptive framing

In this study, the time dimension is partitioned into super-frames, a super-frame into frames and frames into slots The super-frame length is 26.5

ms and seven different coding rates (1/3, 2/5, 1/2, 2/3, 3/4, 4/5, 6/7) are considered; the modulation is QPSK Regarding the frequency dimension, it

is assumed that the total bandwidth can be dynamically segmented, from super-frame to super-frame, and that up to four different carrier types can

be used in a super-frame: 540 kHz (carrier type I), 270 kHz (carrier type II),

135 kHz (carrier type III) and 67.5 kHz (carrier type IV) The roll-off factor

is 0.35, providing symbol rates of 400, 200, 100 and 50 kbaud, respectively The number and type of active carriers is adapted to the traffic requests and the needs of the users, which vary according to channel conditions The transmitted packet can be an ATM cell or an MPEG packet (for numerical evaluations we will only refer to ATM cells) With AC, the length of the slots transmitting such fixed-length packet becomes variable and, therefore, the number of slots contained by a given type of carrier becomes variable, as well Not all the users are necessarily always active Active users are divided into categories, according to both their symbol energy to noise-plus-interference

spectral density ratio, E s /N o,tot and traffic characteristics Traffic is assumed

to be uniform and the considered classes are: Constant Bit Rate (CBR), Variable Bit Rate (VBR), and BE For simplicity and without loss of

gen-erality, one user is assumed to ask only for one of these traffic classes, so that

each user will have allocated slots of a given fixed length on the carrier type

corresponding to its E s /N o,tot [29] Traffic demands are queued according

to the type of DVB-RCS capacity request, which can be CRA, RBDC, and VBDC Capacity requests are prioritized: CRA has the highest priority and VBDC the lowest CBR traffic is assigned to CRA as a whole, whereas VBR traffic is assigned to CRA and RBDC Similarly, BE traffic is also divided between RBDC and VBDC

The number of carriers of each type is computed at every super-frame,

given priority to the users affected by rain Assuming a given E s /N o,tot for the user and some given requests for the current super-frame, a closed-form

estimation of the number of carriers required per carrier type is computed in

terms of an estimation of the number of slots as follows:

n C

n i (s) = n C,CBR

n i (s) + n C,V BR

n i (s) = N C

n i (s)

 (r C CBR +r C

V BR)T s

η i L(η i)



,

i = 1, 2, , N AC

(7.1)

n R n i (s) = n R,V BR n i (s) + n R,BE n i (s) = N n R i (s)

 (r R

V BR +r R

BE)T s

η i L(η i)



,

i = 1, 2, , N AC

(7.2)

n V

i (s) = n V ol

n i (s) + n V,BE

n i (s) = N V

i (s)



V +r BE V T s

η i L(η i)



,

where s is an index making reference to the super-frame, which consists

of 10 frames and lasts 265 ms, n X,Y

n i (s) is the number of requested slots corresponding to capacity request type X (X = C, R or V, which correspond

to CRA, RBDC or VBDC requests, respectively) of traffic class type Y (Y = CBR, VBR or BE) requiring spectral efficiency η i , n X

n i (s) is the total number

of requested slots corresponding to capacity request type X, N X

n i (s) is the number of users requesting capacity type X, T sis the duration of a super-frame

in seconds N AC is the number of possible coding rates, and r X

Y is the bit-rate

requested by traffic class Y that is mapped to request type X V is a possibly

additional amount of bits requested as volume (instead of bit-rate), which

results in n V ol

n i (s) slots, and L(η i) is the length in bits of the packet

The number of carriers of each type is estimated from the total number

of slots needed according to (7.1)-(7.3) The fragmentation of the bandwidth into carriers is performed, starting from the heavy rain-affected users down

to the clear sky ones, while there is still bandwidth available With all these assumptions, a key result has been obtained in [29] by applying cross-layer design for DVB-RCS with AC The user satisfaction strongly depends on the distribution of users relative to the spatial distribution of channel conditions

As a conclusion, smarter scheduling policies should be designed, taking into

An ETSI specification [32] imposes a number of constraints to the problem, namely:

• The total transmission capacity (i.e., carriers) in the satellite beam is divided in areas.

• The symbol rate and slot timing must be the same for all carriers in one

area Coding rates are not necessarily the same

• A given RCST belongs to one (and only one) area and can use only one

carrier at a given time

Hence, it is possible to simplify the problem creating sub-problems, one for each group of carriers of the same type (see Figure 7.7, on the left [9])

It is meaningful to consider that the RCSTs in one area, while transmitting

in a common carrier type, use the same transmission rate Note that the DVB-RCS standard defines an adaptive-coding physical (PHY) layer with several possible coding rates, so the mapping of users to areas is basically defined by the quality of the link (channel conditions) As before, the minimum transmission unit (a layer-2, MAC, packet) can be an ATM cell (53 bytes) or a

Moving Picture Experts Group (MPEG) container (188 bytes) The following

analysis is related to the case of ATM cells

Following the previous discussion, the aim here is to obtain TBTP reduced

signaling for frame description (excessive signaling in the Frame Composition Table, FCT, entails a reduction in bandwidth efficiency) A timeslot with

com-mon duration for all areas is imposed (1), allowing a very simple assignment

1Note that fixing a timeslot duration common to all areas introduces some unused bandwidth that depends on both the timeslot duration and the packet length (ATM cell in our case) However, once a given RCST has been assigned to a certain timeslot, it can change its transmission rate inside the timeslot without affecting the transmission timing of the other RCSTs This argumentation validates the robustness of the solution proposed

Fig 7.7: Scheduling (bandwidth allocation) problem See reference [9] Copyright

c

2006 IEEE.

procedure (after having known the number of timeslots per area): from left

to right and from top to bottom (according to the reading order) Regarding signaling issues, this is translated into a simple FCT, since it indicates the

common timeslot type (which is described in the Time Composition Table,

TCT) and how many times it is repeated in the carrier On the basis of the area rate, one or more ATM cells can be transmitted in a single timeslot

A possible timeslot and ATM cell assignment is shown in Figure 7.7, on the right [9] The problem of how to assign timeslots to areas and ATM cells to RCSTs is discussed later, after introducing the scheduling hierarchy concept [32]

Scheduling hierarchy

The general scheduling problem (which may involve thousands or more RCSTs) may be complex to solve Therefore, it seems reasonable to reduce

it to some smaller problems by imposing some known structure (that can also facilitate signaling) This is an idea similar to that proposed in [33] (particularly in centralized optimization algorithms) According to [32], some

minimum resources are guaranteed to the service providers Since the relative RCSTs for each service provider can be distributed over different areas, in [32] the scheduling hierarchy presents the segment concept, i.e., a grouping of